The matching algorithm used in the ANALYZE program looks at a set of three

vehicles from the ground truth and three vehicles from the vendor classifier at a time. I
performs a search based on time and the number of axles. The result of the algorithm is
one of the following five options: , .

1.

Match - Clear vehicle match found in time and number of axles. Comparison data
entered into the classification matrix, and the length and axle spacing statistics.
Ground truth (tape data) and vendor (classifier) files are both advanced one vehicle.

Sensor Error - Clear vehicle match in time, but not in number of axles.
Classification data stored, but not vehicle length and axle spacings. Ground truth
(tape data) and vendor (classifier) files are both advanced one vehicle.

Missing Vehicle - No vehicle match was found for a vehicle in the ground tmth data.
The vehicle is stored in a separate file and the ground truth (tape data) file is
advanced one vehicle.

Extra Vendor Vehicle - No vehicle match was found for a vehicle in the vendor data
file. The vehicle is stored in a separate file and the vendor data file is advanced one
vehicle.

Split - A vehicle in the ground truth (tape data) file is found to match two smaller
vehicles in the vendor data file. These are stored in a separate file, the ground truth
file is advanced one vehicle, and the vendor data file is advanced two vehicles.

Combination - Two vehicle in the ground truth file are found to match to one larger
vehicle in the vendor data file. These are stored in a separate file, the ground truth
file is advance two vehicles, and the vendor data file is advanced one vehicle.

The algorithm looks only at the time and number of axles of three vehicles from both

the ground truth and vendor data files. In the flow charts on the following pages, the
following acronyms are used:

Vtime[#]- Time of vehicle # from the vendor (classifier) data file.
Rtime[#]- Time of vehicle # from the ground truth (tape) data file.
Vaxles[#] - Number of axles on vehicle # from the vendor data file.
Raxles[#] - Number of axles on vehicle # from the ground truth data file.

<delta>t- Maximum time difference allowed to form match.

215



bad internal wiring connections, Of the eleven classifiers installed, five were malfunctioning;
three were repaired on-site and two were returned to the vendor facility for repair.

The overall conclusion, based on these installations, is that generally a classifier will
require some internal adjustment, repair, or sensor compensation when first installed. The
problems are usually minor and can be easily corrected by a technically qualified installer.
Each system installed for this evaluation was in accordance with the vendor’s specification.
Before the first evaluation was performed, proper operation of each classifier was achieved
and was verified by each vendor.



.

INSTALLATION NOTES

Maxi Replaceable Housing:

The highway surface should be flat and free from excessive irreguiarity. Dishing or bowing
should be limited to (om over the length of the housing.

Mark out two straight parallel lines 60mm apart, with a tolerance of better than 45mm across
the full width of the lsne. Offer up the sensor housing to the desired position and mark out

‘Its length plus SOmm across the paraliel fines, ensuring thal they are perpendicular to the

tratfic fiow. :
Aerosol paint and the use of g straight edge as a masking device will be found to be a good
me

Mark out a further two parallel lines, 25mm apart, using the centre line of the previous lines,
sunning from the nearside of the housing to verge of the road or kerbside. Cut clean vertical
siots on these four marks to a depth of 50mm, -0 +5mm, using a rosdsaw.

Chisel out the gaps between the slots to this depth, ensuring that the base of the rectangular
cavity thus created is reasonably smooth, and never less than 50mm, If a double cutter is
available, chiselling of the narrower slot may not be necessary to create the conduit channel.
Dam off the conduit slot/eensor siot interface to pravent adhesive loss into this gap. Plasticine
of card lg adequate, ,

Remove the spoll from the channels. Blow out all looae dabris with compressed air. la water
lubricated cutterhes beenused, the sist should be dried with a hot airbiower. The siots must
be clean and dry to ensure that sdequate adhesion Is obtained. ~

Ensure that the condult edges are {ree froin burrs which could damage cable. Install the
conduit with one end level with the commencement of the wider channel, The remaining
conduit is buried under verge-side soil or kerbing, with its other end passing into the
weatherproof box containing signal processing equipment via a weather-proot gland. Condult
radii of less than 200mm should be avoided otherwise it may be found that cable passage
will present difficutties.

Conduit materials may vary. but a smooth internal clameter of not fess than 10mm is
necessary. 12mm copper piping or ‘microbore' can provide signal screening, durability
und easy Cabis passage.

Screw meta! plates of approx 100mm tength and 50mm width at right angles across the
housings at intervais of approx 750mm. Small self tapping screws are adequate. The plates
suspend the top surface of the housing flush with the highway surface when the housing is
set into adhesive.

Observing all Health & Safety and Manutacturers instructions, wipe the outside of the
housing with @ cloth wetted with hydrocarbon sofvent to remove dirt and grease.

Thoroughly mix the two components of the mounting adhesive, observing the maker's safety
and handling instructions. An air driven stirrer will be found usetul, A two component 4KG
pack Is adequate for instaliation on one housing of up to 3.5 metres.

Starting at one end, and gradually working across the lane, pour adhesive into the slot to a
depth of 15mm. Place the housing into the channel with the nearside end up tothe dam into
the condult slot. Place weights on the mounting plates to hoid the housing down against the
floating action of the adhesive, and pour adhosive turtherinto the gap between housing and
slot. This should be done slowly and with care to avoid cavitation. There should be sutlicient
spew or excess to ensure the gap is totally full, but this should not be allowed to flow into the
housing channel. It should be noted that the retaining acrews must be downstream of the
fraitic flow, i.e. sloping away from the direction of traffic and not sloping into it,



Figure 45.

axles Spacing Statistics

i
i

0 2.773
30.0-34.9
35.0-39.9
40.0-44.9
45.0-49.9
50.0-54.9
55.0-59.9
60.0-64.9
$5.0-69,9
70.0-74.9
75.0-79.9

>80

Overati = _-0..252

3 3

g SRRGeeEaaeea

8

Wheelbase Statistics

ean

2.773
0.070
0.193

Measurement Accuracy Versus Speed (MPH)
@nd 48-Hour Test

PAT AVC-100 (L-P-L)

Axte_Spacings



11.

12.

14,

15.

16.

Pour the epoxy, and install the sensor. Press the sensor in place, and use a
putty knife to remove the excess epoxy or to apply more epoxy to fill any
voids around the sensor. Smooth the surface of the epoxy even with the
pavement.

Place weights on the leveling plates as required to hold the sensor in place.

Allow the epoxy to cure in accordance with the manufactures directions.
Depending on conditions, torpedo heaters may be necessary to cure the
epoxy in the time allowed before the traffic lane must be opened. The
same cardboard tunnel arrangement used for drying and preheating can be
used for curing.

After the epoxy has cured sufficiently, remove the weights and clip the
wires or plastic ties holding the leveling plates. Remove the plates by
tapping with a hammer. Clip the wires or ties again flush with the epoxy.

Route the coax through the coax slot and fill the slot with 3M Loop Sealer.
Install the coax in conduit (if used) and route it to the equipment cabinet.

Test each sensor using an oscilloscope or by connecting to the classifier.

2.2.2 Loop Installation

The following steps represent a typical installation of an in-pavement loop sensor.
These procedures were followed by each vendor with no significant differences except
the number of turns of wire as noted in the detailed installation descriptions of Section

ry
av.

Locate and mark the loop as in the axle sensor procedure (typically the
loop and axle sensor cut lines are all marked at the same time). Chamfer
cuts are marked at the corners of each loop to facilitate installing the wire.

Make a single cut along each mark using a 1/8 inch saw blade. The cuts
should be one inch deep. Cut a slot to the edge of pavement for the lead
wires. As for the coax cable, make the cut deeper near the edge so that
the wires will exit the pavement well under ground level.

Use compressed air to blow out the water and any debris in the cut. It is
not necessary to dry the cuts.

Starting at the equipment cabinet, route the loop wire (14 AWG type
MTW or THHN, oil and gasoline resistant) along the trench to the edge of

10

oe eo ome oe ee oe ee on oe em oe me



5.2.9.3 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XXVII. The totals for the
entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the

first and last of the seven days.

Table XXVII. Long-Term Count/Classification Accuracy
IRD TC/C 530-4D/4P/4L (PR-L-PR)

Total Total
Difference Percent
1669 102.80

k

N/A N/A

l 4 104.12
| Class 2 | 29377 39427 -10050 7451 7439 75.20
Class 3 18134 7558 10576 239.93 28.11 207.44
Class 4 | 134 39 95 343.59 233.33 228.57
Clas 5} 1855 n9 1136 258.00 141.28 261.19
Class 6 729 686 8 106.27 110.64 108.7
Class 7 9 127 “118 7.09 2721 9.99
Class 8 832 1061 229 73.42 97.87 90.27
Class 9 9627 7326 2301 13141 144.44 12730
Class 10 107 279 Re 26.67 26.56
Class 11 42 386 -16 76.10 100.00 90.00
2.33 28.57 2131
0.00 0.00 0.00

139



Table XXV. Accuracy Summary for IRD TC/C 530-4D/4P/4L
(PR-L-PR) 1st 48-Hour Test

50-59
60-69
70-79
80-89

65.6
714
738

83.6
90.2
919

0.716

0.637

11.485
11.967
11.523

| Pav Temp
60- 69
70-79
80- 89
90- 99
100-109
110-119

4
82.5

93.8

0.196

0.135
0.169
0.167

0.761
0.584
0.322
0.764
0.511

-2.414

7947

11.533
11.326
12.690
12.650

134



=—_ ese et a a oe oe ee ae ee ee oe oe

Contract Research
GDOT Research Project 9210
Final Report

ACCURACY OF TRAFFIC
MONITORING EQUIPMENT

By:

Bruce A. Harvey
Glenn H. Champion
Steven M. Ritchie
Craig D. Ruby

Prepared for: Project Funded by:

Georgia Department of Transportation Federal Highway Administration
Office of Materials and Research Office of Highway Information Mgmt.
15 Kennedy Drive 400 Seventh Street, S. W.

Forrest Park, Georgia 30050 Washington, D. C. 20590

Submitted by:

Communications and Networking Division
Information Technology and Telecommunications Laboratory
Georgia Tech Research Institute
Georgia Institute of Technology
Atlanta, Georgia 30332-0821

Technical Report
GTRI Project A-9291

of this report reflect the views of the author who is responsible
for the facts and the accuracy of the data presented herein. The contents do
not necessarily reflect the official view or policy of the Department of
Transportation or the Federal Highway Administration. This report does not
constitute a standard, specification, or regulation.

The contents



Figure 43.
PAT AVC-100 (L-P-L)

Axles Spacing Statistics
Speeds Mean sto

0.498 0.507 Ww 9
x 0.228 3 3
35 W %
40 2% 51
cu 134 262
50 825 1794
35 2860 6104
60. 4815 9m%S
6. 38635859
70. 843 1028
re] Riad W2
roy roy
Overalt 13600 25079
‘Speeds Mean sTD Vehicles

0.507 19

0.228 3

0.317 W

6.507 a

0.379 14

0.510 825

9.378 = 2860

0.786 4815

0.762 «= 3863

2.665 863

0.671 59

0.664 24

4.353 13600

-
g

Measurement Accuracy Versus Speed (MPH)
- Ist 48-Hour Test

Ld

m on ok om ow we

om


4. RATAREDUCTION AND ANALYSIS

4.1 | THE COMPUTER VEHICLE CLASSIFICATION AND REDUCTION SYSTEM
(CVCRS)

The CVCRS is a PC-based system designed to assist in the collection of detailed
vehicle classification, length and axle spacing from video tapes of the traffic stream. The
video tape of the traffic stream taken from the utility pole off the side of the roadway (the
pole camera - see Figure 21) is displayed on a second monitor connected to a video
Processor card in the PC. The video is paused by the user when a vehicle enters the test
area, The locations of the front and back bumpers, and the axles are then entered using the
mouse on the PC and.a crosshair displayed on the monitor. The software calculates the
overall length of the vehicle and the axle spacings, and then makes an initial estimate of the
vehicle’s classification. The user has the option of accepting or modifying the classification
of the vehicle based on the FHWA guidelines for vehicle classes. The CVCRS also reads
the time recorded on the videotape and time stamps the vehicle recorded for comparison
with the data from the vendor’s classifiers. Calibration of the CVCRS system length
measurements is done using a 40 foot box marked on the pavement and a calibration
Toutine in software which accounts for the camera angle and distance.

4.1.1 Hardware

The CVCRS hardware includes a video cassette recorder (VCR), a personal
computer with mouse (PC), a Data Translation DT3851A-1 Flexible Frame Processor (PC
video card), and a second VGA monitor. A picture of the CVCRS hardware is shown in
Figure 22. The PC video card is installed in the PC and receives input from the VCR
(lower right). The PC video card displays the video on the second VGA monitor (right of
the PC) along with a crosshair cursor used to make measurements. Use of the video card
allows the overlay of the crosshair cursor and automatic measurement of vehicle lengths and
spacings by simply pointing and clicking with the mouse. The software required to operate
the video card and record the vehicle data is installed an run on the PC.

The monitor and VCR shown on the left in Figure 22 is used for monitoring lane
changes within the test site. The process used to handle vehicles which change lanes within
the test site will be discussed below in Section 4.2.

4.1.2 Software

Custom software was written to setup and operate the CVCRS hardware. The
primary purposes of the software were to operate the Data Translation PC video card,
calibrate the length measurements, assist in the measurement of vehicle lengths and axle
spacings, record the time at which the vehicle entered the test site, and make an initial guess
of the vehicle class. The software ("CVCRS.c") was written using the C language and the
Microsoft C compiler.

53



[Wtime[S) - Reinmee[3}]
~
[Vtiene[3} ~uel,

Yes



Axles Spacing Statistics

Speeds

<0
30.0-34.9
35.0-39.9
40.0-44.9
45.0-49.9
50.0-54.9
55,0-59.9
60,0-64.9
65.0-69.9

Mean STD Veh
4.584 7.571 3
8.169 5.037 3
0.000 0.000 0
0.061 0,544 "1
0.099 0.324 wy
0.107 0.377 S32
0.100 0.386 ©1950
0.087 0.366 4399
0.085 0.357 = 4320
0.086 0.351 1655
0.090 0.260 260
0.095 0.489 42
0.099 0.515 13264
Mean $TD = Vehicles
7.757 15.932 B
29.953 3.479 3
0.000 0.000 0
0.09% 0.562 "
0.151 0.288 79
0.192 0.348 532
0.177 0.356 1950
0.150 0.305 4399
0.121 0.317 4320
0.099 0.335 1655
0.096 0.261 260
0.095 0.489 42
0.153 0.783 13264
Figure 57.

IRD TC/C 530-4D/4P/4L (PR-L-PR)

axte_spacings

137

Length Statistics
Mean = STD Vehicles

12.499 32.407 7
3

0

Ww
nr
532
1950
4396
6319
1655
260
ai

13253

Length Percentile Statistics

Mean = $TD Vehicles

270.92 365.99 7
208.355 1.714 3
0.000 0.000 0
1 4
79
532
1950
4396
4319
1655
260
41

13253

Measurement Accuracy Versus Speed (MPH)

2nd 48-Hour Test



listed. The overall (independent of speed) mean, standard deviation and vehicle totals are
listed for each measurement. If applicable or existing information is available, the following
statistics are calculated and listed in the file TABLE.OUT:

© Axle Spacing- True (ground truth) length less the measured length (classifier)
in feet,

@ Wheelbase - True length minus measured length in feet,
© Overall Length - True length minus measured length in feet,

© Overall Length Percentage - True length times 100 and divided by the
measured length.



Page 3

one along each edge - maintaining a depth of 1%" to 2".
Extra care must be taken with regards to cut depth when
using abrasive blades, since they wear rather quickly.
The recommended depth must be maintained in the guide
area. It may be necessary to extend the end by a few
inches so that this depth is maintained. Next cut the cable
slot for the lead wire. In this case, the painted area
should be cut out. Ensure that the cable slot is centered
on the sensor slot and should be at least 3 inches deep.

Once the cutting is done, chisel out the center (remaining)
section of the road, as shown in Figure 5. If wider blades

fF CUT OUT UNPAINTED AREA ONLY are used (approximately ‘4" wide) some contractors prefer

Figure 4 :Carefully cut at an even depth

between the lines.

cutting out the center section with the saw. This is
certainly acceptable, though care should be used to ensure
the cut depth remains the same. The end result of all of
this hard work, dust

and toil will a channel cut in the road, as shown in Figure
6. Blow out or sweep out large debris from the channel.
Get the sensor and place it in the slot to ensure proper fit
- re-work if necessary. Now with a wire brush, rough up
the sides and bottom of the sensor slot ensure good
adhesion of the epoxy compound.

There are two recommended ways to mount the sensor.
The first is to use cement anchors and Jarge head flat head

CHISEL OUT CENTER AREA

CHISELED OUT CHANNEL

Bg ReDTy, D,
SE ey ene
Figure 6: This is the end result
of all the hard work

screws in the bottom of the
channel. The sensor will
Test on these screws, as

shown in Figure 7. Using ~~
the cement anchors and
screws, drill the holes in Figure 5: Chisel out the center area to
the bottom of the channel an even depth

to accommodate the

cement anchors, at about 1%’ from each end of the slot.
Following the manufacturers instructions for the anchors, insert
the anchors in the holes, and screw then down sufficiently to
ensure that they are correctly installed. Now clean out the

* channel using compressed air or a portable blower. If these are

unavailable, use a broom, but really sweep hard to ensure the
channel is clean.

The second option for mounting the sensor is to use the supplied brackets to hold the sensor in
place from the top. This is the recommended option, and will be discussed in more detail later.

The slot is now ready for mounting the sensor. If the temperature is below 60° F, it may be

Eif Atochem Sensors Inc, PO Box 799, Valley Forge, PA 19482 * (215) 666-3500 Fax (215) 666-3509



Table XXII. .
Table XXII.
Table XXIV.
Table XXV.
Table XXVI.
Table XXVII.
Table XXVIII.
Table XXIX.
Table XXX.
Table XXXI.
Table XXXII.
Table XXXII.
Table XXXIV.
Table XXXV.
Table XXXVI.
Table XXXVI.

Table XXXVI.

Table XXXIX.
Table XL.
Table XLI.
Table XLII.

LIST OF TABLES (cont.)
Accuracy Summary for TimeMark Delta T ........-.-.++- 125
ist 48-Hour Test
Accuracy Summary for TimeMark Delta T ........-..---- 129
2nd 48-Hour Test
Long-Term Count/Classification Accuracy .........-.---+- 130
TimeMark Delta I
Accuracy Summary for IRD TC/C 530-4D/4P/4L ........-- 134
(@PR-L-PR) 1st 48-Hour Test
Summary for IRD TC/C 530-4D/4P/4L ........-- 138
(PR-L-PR) 2nd 48-Hour Test
Long-Term Count/Classification Accuracy .........---+++- 139
IRD TC/C 530-4D/4P/4L_ (PR-L-PR)
Accuracy Summary for IRD TC/C 530-4D/4P/4L .........- 143
(P-L-P) ist 48-Hour Test
Summary for IRD TC/C 530-4D/4P/4L ........-- 147
(P-L-P) 2nd 48-Hour Test
Long-Term Count/Classification Accuracy ............-45- 148
IRD TC/C 530-4D/4P/4L (P-L-P)
Accuracy Summary for Golden River Marksman 660 ........ 152
2nd 48-Hour Test
Long-Term Count/Classification Accuracy .........-....+- 153
Golden River Marksman 660
Accuracy Summary for Diamond TT-2001 ..............--- 157
(Autologger) ist 48-Hour Test
Accuracy Summary for Diamond TT-2001 .........-.....+ 161
(Autologger) 2nd 48-Hour Test
Long-Term Count/Classification Accuracy .........-...--- 162
Diamond TT-2001 (Autologger)
Accuracy Summary for Diamond TT-2001 ..............-- 166
(Philips) 1st 48-Hour Test
Accuracy Summary for Diamond TT-2001 ..............-- 170
Philips) 2nd 48-Hour Test
Long-Term Count/Classification Accuracy ..............-- 171

Diamond TT-2001 (Philips)
Classification Accuracy ........-----+--+---> Vette eee
Accuracy of Axle Spacing Measurements
Overall Length Measurement Errors ......
Overall Length Measurement Percentiles

om i — on ao oe Z mTM

Y

oa wa

—_ aa



—+(us)

Ne
‘Yes

216

Yes
Vaxies[1] = Raxies[1] ?
. No

Vtime[1] = Rtime[t) ?



Question 11, Does the accuracy change over time? Is the accuracy the same when the
: is first installed and when itis picked joes the Jength of
time in Operation affect the equipment?

The two detailed 48-hour tests were conducted approximately 4 months apart.
Between the tests, the sensing devices remained in the roadway and were subjected to
normal traffic volume. Comparing the classification accuracy of the each vendor classifier
in the first and second 48-hour test can be accomplished by reviewing Table XXXIX (of
Question 1. above), No Piezoelectric sensors were replaced between the two tests, but some
piezoelectric sensors did fail. Those classifiers which used the failed sensors were not
included in the second test and their results are not included in the table.

Nearly all of the classifiers had nearly equal to or better vehicle classification
accuracy during the second 48-hour test than during the first test. The only notable
exception to this pattern was the Diamond TT-2001 which had a software upgrade between
tests that included a data recording bug. Using lessons learned during the first test, greater
care was taken during the second test to prepare the piezoelectric sensors. Where axle
sensors were installed low in the pavement, or where piezoelectric output was low, bituthane
tape was placed over the sensor to increase its output voltage levels. This resulted in a
lower sensor error (miscounted axle) rate during the second test and a corresponding higher
percentage of correctly classified vehicles. The axle sensor accuracy appeared to have a
greater effect on classification accuracy than time, and the sensor accuracy was dependent
primarily on installation and preparation prior to each test.

Axle spacing and overall length measurement accuracy revealed no noticeable trend
between the first and second 48-hour test. Almost all had mean errors which remained
nearly constant between the tests.

An assessment of the accuracy over tim ring a continuous test can be made

An assessment of the accuracy over time during a continuous test can be made by
reviewing the results in Section 5.2 of the 7-day test results for each vendor. No specific
trends were noted in the accuracy of the classifiers over the 7-day test. Some classifiers
displayed some accuracy improvement from the first to the last day of the test, but others
showed some degradation. Therefore, the classification accuracy as a function of time over

a seven day period depended on the particular classifier and no overall trends were noted.

182



5.2.7 Electronic Control Measure HESTIA

The Electronic Control Measure model HESTIA classifier used a P-L-P sensor
configuration with ECM PB2N33/25 piezoelectric axle sensors. The results of this classifier
are presented below.

5.2.7.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 46. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 67.5% of the vehicles (86.4% if class 2-3
errors not included). The number of vehicle axles was miscounted 10.05% (percent sensor
errors) of the time. About 2.2% of the vehicles classified by the HESTIA were the result
of a suspected split or combination.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 47. The HESTIA classifier measures axles spacings, wheelbase length, and overall
vehicle length. The measurement error statistics (mean and deviation) for al}
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XIX contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement |
temperature.

113



Length Statistics

axles Spacing Statistics

Speeds Mean = STD

Vehicles

STD

Veh axte_Spacings

hecooreronmys

g

BB88888e8ER8

agqauaaen!

jeseaeaane
ASISAS 3x

B6
a

200GrGronmys

x
gooeerorcnns
g

Resss8ssseas

fsodeaccadceer
38382035
sScddeeddaee

Seeedegece

go222232335

BSVRRSSEK

3.073 12848

2.232

Overall

12848-22195

1.519

0.644

Overall

Length Percentile Statistics

Wheelbase Statistics

Vehicles

sTD

Vehicles

sTD

Mean

RHSTRRISER

RoeocCoOrcCreoNnMmsy
5 2
x
ecesenssent
ESSE88888238
pegegaccsaas
ceeceene
RESESR SSSR EE
SSocdesodoors
8
& 0, 0 0 0 & 0, 9. &
ASIGRSISHE
§aeegeagseass
BASS

16.07 12848

114,30

Overall

12848

20.127 19.208

Overall

Measurement Accuracy Versus Speed (MPH)

ECM HESTIA - 2nd 48-Hour Test

Figure 49.

119



i
L

INTERNATIONAL

TECHNICAL BULLETIN

- READY-SET PAVEMENT GROUT ~

DESCRIPTION: READY-SET Pavement
Grout is an epoxy compound designed for

use in sealing sensors into roadway surfaces. ~

lt can be traffic ready in 1/2 hour if all of the
recommendations in this report are followed.
tt is supplied in a kit which contains:

A) 5-gallon pail of graded aggregate.
8) 1-galion pail of epoxy (Part A).
C) 1-quart can of hardener (Part 8).

When cured, the epoxy product produces an
environment for the sensor which protects It
against snow, ice, rain, salts, chemicals,
abrasion and temperature extremes.

APPLICATION: READY-SET Pavement
Grout is supplied in a kit which measures
1.625 gallons or 375 cubic inches. This
amount of material is sufficient to set one 6'4”

sensor. Two kits are required to set an 11°10”
sensor.

USING THE KIT: As mentioned in the
description, the kit contains one 5-galion pail,
one 1-gallon pail and one 1-quart can. Open
the 1/2 full galion of epoxy. Remove the lid
from the quart can of hardener and pour the
hardener (Part B) into the epoxy (Part A)
contained in the galion pail. Stir them
together for 2-3 minutes, either with a stirring
stick or with power stirring. Take care to
scrape the sides and bottom of the 1-galion
pail during the 2-3 minutes of mixing. Use the
stick which is provided for this purpose. After
thoroughly blending the epoxy with the har-

dener, transfer this blend immediately into the
5-galion pail of graded aggregate and begin
power agitation. Continue blending the aggre-
gate with the blended epoxy for 2-3 minutes.
Once again, scrape the wails and bottom of
the aggregate mix to insure a full wetting of
all of the aggregate.

Know the air temperature. A thermometer is a
handy tool for this purpose AND it should be
used. Consult the following graph to deter-
mine the waiting period necessary before
potting the sensors in their prepared groove.
The graph shows the approximate waiting
time and could vary upward in time if the wind
velocity Is over 5 MPH. For example: If the air
temperature is 60°F., the graph states that
you should wait 25 minutes before potting the
sensors. Adding the time that it takes to do
the potting, the epoxy will be ready for traffic
in 1/2 hour,

fare] WAITING TIME AFTER MIXING

al

:

s

» NS

>

2

we

ad am

: Ko,
“« LJ o Tr LJ .] 100

ENGINEERED EPOXY SYSTEMS



Table XXXIX. Classification Accuracy

Equipment
_ Vendor _

LP-L
(@hilips)

703 (82.5)
635 (78.8)

P-L-P
(Philips)
P-P
(Philips)
P-P
(Philips)

75.3 (93.0)
748 (93.2)
73.7 (90.1)
79.0 (96.2)
71.1 (92.4)
79.1 (96.2)

PAT
Equipment
Corporation,
Inc.

AVC-100

AVC-100

P-L-P
(Atochem)
LP-L
(Philips)

N/A

N/A.
76.6 (95.0)
76.6 (95.1)

MITRON
Systems
Corporation

MSC-3000
DCP

P-P
(Autologger)

Ne lye Ne bye Nene [Ne

N/A
N/A

Electronic
Control
Measure

HESTIA

P-L-P
(ECM)

675 (86.4)
72.0 (94.3)

Delta I

P-P
(Philips)

78.9 (94.4)
773 (94.6)

TC/C 530-
4D/4P/4L

PR-L-PR

(Dynax)
P-L-P

(Philips)

69.3 (88.4)
72.6 (92.9)
70.8 (89.7)
73.8 (93.9)

Traffic Ltd.

P-L-P
(Traific)

N/A
63.9 (82.3)

Diamond
Traffic

P-L-P
(Autologger)
P-LP

WAN RN LN INE Ne Le

73.1 (92.0)
11.0 (11.8)*
755 (93.9)

13.0 (16.2)*

174



5.2.13 Diamond Traffic Products (Philips Vibracoax)

The second set of sensors (also in the P-L-P configuration) used with the Diamond
Traffic Products model TT-2001 classifier used Philips Vibracoax axle sensors. The results
of this classifier using the Philips axle sensors are presented below.

5.2.13.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 68. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 75.5% of the vehicles (93.9% if class 2-3
errors not included). The number of vehicle axles was miscounted 3.47% (percent sensor
errors) of the time. There were less than 0.5% of the vehicles classified that were the result
of a suspected split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 69. The TT-2001 classifier measures axles spacings, wheelbase length, and overall
vehicle length.’ The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XXXVI contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

163



The program then informs the user of the start time of the input file and prompts the user
to input the time to start the binning. The start time input by the user is primarily used to
get the program to bin at even times such as every quarter hour. The start time is assumed

45 be for the same day. Yf the user enters 4 start time before the innit Sle start time. the
(6 oe 16F Wie SAME Gay. a WE WSET EHLETS 4 Stari tiie GEIOTE Wie iipiit we Start time, we

output file will contain al] zeros for those intervals before the interval containing the first
vehicle in the input file.

The BINNED program was the primary analysis software for comparing the long
term statistics of the data from the 7-day test.

4.5 THE "ANALYZE" PROGRAM

The ANALYZE program was the primary tool for analyzing the detailed
performance of the vendor classifiers on a vehicle-by-vehicle basis. This program contained
an algorithm which matched the vehicles from the tape data (ground truth data) to those
from the vendor files. After matching the vehicles, the program collected statistics of
classification accuracy, overall length measurements, axle spacing measurements and
wheelbase measurements, The output of the program is a set of files containing tables of
results and examples of suspected splits or combinations of vehicles by the classifiers. A

split occurs when a classifier claccifiec a cincle vehicle as two separate. smaller vehicles. a
Spat OCCUIS WHER & CiasSHier Ciassiies @ SIngse VEmmCc as two Separate, SMauer venicies. 2

combination occurs when two vehicles are classified a single larger vehicle by the classifier.

The ANALYZE program looks at the data from three vehicles from the ground truth
file and three from the vendor classifier file at a time. The input files are assumed to be
in the standard format and the clocks are assumed to be synchronized. If the clocks are not
synchronized, then differences must be determined manually and adjustments made to the
vendor data file. The program will attempt to find the best match between the ground truth
vehicle and one of the vendor vehicles, The best match is made based on time and number

of axles. A flow chart of the vehicle matching algorithm of the ANALYZE program is
shown in Appendix C.

The user can set a maximum time differential to be used when determining that a
ground truth vehicle and a vendor data vehicle match. For this project, the maximum time
differential was set at 2 seconds. If no unmatched vendor vehicle was within the maximum
time differential of an unmatched ground truth vehicle, then that ground truth vehicle was

declared to be a Missing vehicle (missing from the vendor file). If no unmatched ground
truth vehicle was within the maximum time differential of an unmatched vendor vehicle,
then the vendor vehicle was declared to be an Extra vehicle. Missing and Extra vehicles
most often occurred when vehicles changed lanes, or when the vendor equipment or the

pole camera was not operating for a short period of time.

The ANALYZE program was designed to give the vendor classifier the benefit of the
doubt when performing vehicle matching. The program seeks a match where the time

difference is minimized and the number of axles is the same. If the number of axles differs

39



INTERNATIONAL ROAD DYNAMICS INC.

CORPORATE OFFICE: 702 43rd Street East, Saskatoon, Saskatchewan, CANADA 87K sTo
Telephone: (S06) 653-6600 Facsimile: (806) 242-5599

Read Material Safety Data Sheets (MSDS) as provided

a) Avoid breathing grout vapors.
b) Do not use in enclosed areas. Always ensure adequate ventilation.

¢} Do not use BPO powder near heat or open flame. BPO is a very powerful oxidizer
{it supplies its own oxygen when burning).

d} Use dust mask If required to prevent inhalation of BPO.
Wash skin if contacted by powder.

e) Always wear appropriate protective clothing, boots, coveralls, gloves
and safety glasses.

CLEAN-UP

Wash any uncured grout from tools and equipment with water.
After curing, grout can only be removed by mechanical means.

ta.:Doe Saves 633
*3¢ Fev 6 Fous3



PEEK TRAFFIC INC.

le 10-157 a}

fo— 10-01" ~

ae rrr

ba 7
— ee re

w PY u | P2 TPs 5
jt sse 4 a}
fl aL
T 7-17 4 rae) ON ra vo aN i
47 | 300 |
war / \ | \ }
1! 7 \ oN
v \ NY
N 1 Y
a | 4
aN ~ \ yY a
~~ \ Y
~N a
~ ~~ { 4
7
EQUIPMENT
Note: All loops , CABINET
are 5X 7,
and all sensors
ore 5'-6.6" tong
Drawing

Figure 5. Peek Installation Configuration

17



NOMINAL INSTALLATION TIME
Approximately 4 hours for permanent sensors and 15 minutes to set up
configuration.

INSTALLATION PROCEDURE
Attach loops, tubes, or piezoelectric sensors.

SOME STATES CURRENILY USING THIS EQUIPMENT
Arkansas, Georgia, Illinois, New York

GTRI COMMENTS
Gin COMMENTS

Piezo-Loop-Piezo

210

im a i ae a

—_ = a oe oe a ee oe



Axles Spacing Statistics

Speeds fean —$1D Veh Axte_specings
8.000 9.000 t) °
0.010 0.050 2 2
0.133 0.127 3 7
0.017 0.228 6 2

0.084 1.351 3001 6091
0.080 0.567 1335 1947
0.113 0.489 ehh 272
0.169 0.247 3B s

0.098 2.722 8213 17159

Wheelbase Statistics
Speeds Mean s1D Vehicles

<0 0.000 0,000 o
30.0-34.9 -0.010 0.050 2
35.0-39.9 0.377 0.184 3
40.0-44.9 0.033 0.407 6
45.0-49.9 0.483 1.790 27
50.0- 02 2.246 198
35.0-5 683 16.064 976
60.0-64.9 0,105 1.072 wes
65.0-69.9 0.170 4.859 3001
70.0-74.9 0.117 0.710 1335
75.0-79.9 0.126 0.5246 hk

>80 0.169 «0.247 3
Overalt 0.206 5.702 8213

Figure 37. Measurement Accuracy Versus Speed (MPH)
Peek GK-6060 (Lane 2) - ist 48-Hour Test

88



MITRON SYSTEMS CORPORATION

«
PI pal
Ww
47
+s
; T
p00 | |
10-30"
| |
|
T
/
\ /
\ /
\ /
\ of
\
Note: Both sensors
are B-4.2" iong 4
EQUIPMENT
CABINET

Figure 9.

2A

Mitron Installation Configuration Drawing



_

==

Vibracoax sensors are rugged sensors and if installed properly in a
Pavement they can last for several years delivering good signals.

Nevertheless construction work on highway is not always easy and
particularly the use of excessive heating with powerful gas burner can
damage the coaxial extension cable.

Then we recommend that immediately after the installation the electrical
characteristics of the Vibracoax sensors are thoroughly checked: insulation
resistance, capacitance, generated voitage (in this order).

INSTRUME:

° Insulation Resistance: ohmmeter capable of reading at least 20
Megohm.

° Capacitance: Capacitance meter capable of reading at least 30
nanofarad.

° Voltage: voltmeter capable of reading millivolts D.C.

TESTS

All the electrical tests are done between the core and the screen of the
extension cabie.

ILL Insulation Resistance (IR)

The insulation resistance must be found higher than 1,000,000,000 ohms
(1,000 Megohm) on new sensors. ,

Practically many multimeter read up to 20 Megohm. If the IR is higher than
20 Megohm the sensor passes the test.

rf ayaa 1000 ohme thic pone the avtencian eahies u
lf the IR is lower than 1,000 ohms this means the extension cable was burnt

by a severe heating. (the internal insulation material melts and the cable core
moves toward the screen resutting in a short-circuit). Locate the defect and
repair the cable if possible or the sensor has to be replaced.

F002

AUTHOR: GB PAGE: : 2/3
CODE: VB 901 D002 | REV: O

THERMOCOAX NORCROSS



YOSNAS OZAld Sdi Hd

«OC

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088"

|_|

TANNVHO 55
WANIIN TW O08 INVXI74
XVOOVHEIA AXOd4 GNVS

; aNnoaWoo NOILW INSdVONA



5.2.11 Golden River Traffic Ltd. Marksman 660

The Golden River Traffic Ltd. mode Marksman 660 classifier used a P-L-P sensor
configuration with Traffic 2000 axle sensors. The results of this configuration are presented

below.
5.2.11.1 First 48-Hour Test

The classification equipment was not functioning at the time of the running of the
first 48-hour test. Therefore, no data was collected or reduced for this test.

5.2112 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 62. The classification matrix is presented in bath absolute numbers, and

percentages.

The classifier correctly classified 63.9% of the vehicles (82.3% if class 2-3 errors are
not included). The number of vehicle axles was miscounted 7.91% (percent sensor errors)
of the time. There were less than 1.0% of the vehicles classified that were the result of a

suspected split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 63.

The Marksman 660 classifier measures axle spacings and wheelbase length. The
measurement error statistics (mean and deviation) for al] measurements are included in the
figure as a function of measured vehicle speed (mph). Note that all measurements are in

feet.

Table XXXI contains a summary of the results of the classification accuracy as a
function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

149



e. i - The memory in this unit filled more
quickly than expected in the carly part of this test. Approximately ; 24 minutes
of data collection was lost when the memory filled up before it could be
downloaded to a PC. The download cycle was shortened from 4 to 3 hours
to avoid this problem for the rest of the test.

3.2.2 Second 48-Hour Detailed Test
3.2.2.1 Test Date and Conditions

The second 48-hour test was conducted September 9 - 11, 1993, The air temperature
during the test ranged from 62 degrees F to 84 degrees F. The pavement temperature
ranged from 61 degrees F to 110 degrees F. The weather was partly cloudy and there was
no precipitation during the test. This test was scheduled in the hopes of rainfail, but the
only rain was a brief sprinkle which did not register on the rain gauge or significantly
moisten the pavement.

The traffic during the test was typical weekday traffic for the site. There was no
traffic congestion during the test and the average speed of traffic was typically near
65 MPH. The ADT in the test lane (as determined from the video data reduction) was
approximately 10,600 vehicles. The ADT was higher during second 48-hour test because it
was near the Labor Day holiday.

3.2.2.2 Participating Vendors

All of the classification equipment listed in Table I was included in the second 48-
hour test except the Mitron Systems MSC-3000. Failures in the piezoelectric sensors used
by the Mitron classifier resulting in the vendor electing to withdraw from the remaining
tests. The Golden River Traffic Marksman 660 was repaired and participated in this test.
The Diamond Traffic Products TT-2001 received a software upgrade (new ROMs) between
the first and the second tests. The upgrade had a bug in the data recording algorithm which
resulted in errors in the data file stored by the unit. All of the remaining classifiers were
operated in the same way as they did in the first 48-hour test.

The augmented road tube test was conducted in parallel with the second 48-hour test.
Two road tubes were installed across the outside lane of the highway and two were installed
across both lanes of the highway. The classifier used for this test was a Peek TrafiCOMP
Il (Peek 241) supplied by the Georgia DOT. The intent of the test was to determine how
accurately the road tubes could monitor traffic in multiple lanes, particularly in heavy traffic.

3.2.23 Problems and Exceptions to Test Procedures

During the second 48-hour test, the main problem was an incorrect configuration of
the lane-change camera and recorder. The camera used for recording lane changes did not

49



Application Note Number 27 (7/92)
INSTALLATION INSTRUCTIONS

ROADTRAX SERIES ’P’
PIEZOELECTRIC TRAFFIC SENSORS

The Elf Atochem Sensors Inc Roadtrax® Series P Traffic Sensor is a Permanent, In-The-Road,
Class I traffic sensor for vehicle classification and counting. The sensor consists of an outer
aluminum channel to define the area of the sensor, a molded polyurethane elastomer to protect
the sensor, and finally a sensor element. The sensor material is a space age polymer -
Polyvinylidene Fluoride or PVDF. PVDF, when it is specially processed during manufacturing
via a mechanical orientation and electrical polarization process, is piezo electric, and converts
mechanical energy into electrical charge when a stress is imparted on it. Although the actual

voltage output will vary based on many parameters, it is typically measured in the range of a
few 100 millivolts to volts.

INSTALLATION PREPARATION: The installation site should be carefully chosen.
Excessive pavement rutting may result in sensor damage or improper sensor operation. Sites
where rutting exceeds 14" under a 3” straight edge should be avoided. The pavement should be
checked for adequate depth and structure, as well as having acceptable feeder cable routes and
junction box location. It may also be beneficial to observe the traffic flow patterns of a
proposed site over a period of time to ensure proper sensor placement. The best results in terms
of uniformity of signals will result from sensors which are placed on straight and level roads.

Sensor installation must be carefully coordinated with proper road management, ensuring that
all local regulations are complied with for road
closure and hazard marking. Although traffic
data is very important, it is not worth the life of

a installation crew member. So please, ensure oN . ¢c
that adequate traffic control is in place, and that | ns
safety is taken very seriously. Loe sme moss ener.

5

INSTALLATION: First, it is necessary to
mark the road for the location of the sensor.
The sensor must be laid perpendicular to the
flow of traffic. To assist in doing this iS

accurately, use a lumber crayon and mark an x" Figure 1: Ensure that the sensor is perpendicular to
on the road at position "A’* (Figure 1). Next, the flow of traffic.

ROAD SURTACE

EM Atochem Sensors Inc, PO Box 799, Valley Forge, PA 19482 ® (215) 666-3500 Fax (215) 666-3509



LIST OF PARTICIPATING VENDORS AND CONTACT PERSONS

DIAMOND TRAFFIC PRODUCTS
P.O. Box 975
Port Richey, FL 34673-0975

DOCAL ASSOCIATES, INC.
Suite 211, 264 Amity Road
Woodbridge, CT 06525

ELECTRONIC CONTROL MEASURE
P.O. Box 888
Manor, TX 78653

GOLDEN RIVER TRAFFIC LIMITED
c/o B B K ELECTRONICS, INC.

9470 Sacramento Drive

New Port Richey, FL 34655-1619

INTERNATIONAL ROAD DYNAMICS, INC.
702 43rd Street

Saskatoon, Saskatchewan

Canada S7K 3T9

MIKROS SYSTEMS
P.O. Box/POSBUS 20309

MITRON SYSTEMS CORPORATION
2000 Century Plaza
Columbia, MD 21044

PAT EQUIPMENT CORPORATION, INC.

1665 Orchard Drive

Chambersburg, PA 17201-9206

189

Jerry Schiff (813) 843-0270
FAX (813) 843-0270
TT-2001 Classifier
Tony Docal (203) 387-3218
FAX = (203)387-4957
Autologger Sensors
Ron White (512) 272-4346
FAX (512)272-5161
HESTIA Classifier
Bob Klaush (813) 376-5661
FAX (813)372-6918
Marksman 660 Classifier

Rod Klashinsky (306) 934-6777
FAX (306) 242-5599
TC/C 530 Classifier

+27 12 73 1010
FAX +27 1273 4646
TEL-2CM Classifier

Johan Steyn

Donald Dixon (410) 992-7700
FAX (301)596-5119
MSC-3000 DCP Classifier

Siegfried Gassner (717) 263-7655
FAX (717) 263-7845

AVC-100 Classifier



Axles Spacing Statistics

Speeds

<0
30.0-34.9
35.0-39.9
60.0°44.9
45.0-49.9
50.0-54.9
55.0-59.9
60.0-64.9
65.0-69.9
70.0-74.9
75.0-79.9

>80

Overall

Mean sTD Veh
2.115 5.082 8

0.159 0.578 = 9573

Wheetbese Statistics

Speeds

Beil
30,0-34.9
35.0-39.9
40,0-44.9
45.0-49.9
50.0-54.9

Mean sTo Vehicles

Axle_Spacings
uN

Length Statistics

Mean

i

3.019
0.000
8.770
2.952
-1,006
+0.370
°0,683
0.712
-1.878
2.728
+2.037
80 +1830

&

AIRSASRSAS
bobescoece
SRESESESESE
woevovoe0”

Overall -1,321

$TD

1.619
11,302

Vehicles

Length Percentile statistics

Speeds Mean

<0 60.71
30.0-34.9 0.000
35.0-39.9 147.663
£0,0-44.9 129.169
45.0-49.9 104.251
50.0-54.9 105.518
55.0-59.9 105.300
60.0-64.9 102.362
65.0°69.9 96,574
70.0-74.9 88.465
‘%5.0-79.9 89.575

‘BO 91.12

Overall 98.35

Pigure 55. Measurement Accuracy Versus Speed

IRD TC/C 530-4D/4P/4L (PR-L-PR)

133

- Ist 48-Hour

STD

67.81
0.000
0.040
102.212
56.669
63.187
64,520
59.012
42.851
19.976
21.583
14.65

51.68

(MPH)
Test

Vehicles.



PAT EQUIPMENT CORPORATION, INC.

w-50" 16-50"

Note: All loops
are 6 X 6,

EQUIPMENT
CABINET

ond oll sensors

ore 6'- 3.6"

Figure 7.

tong

, PAT Installation Configuration Drawing

20

ee ee ee ee ee

om



of the 7-day test (after the second 48-hour test). The classifiers where converted to a
binning mode (rather than vehicle-by-vehicle mode), and the pole and Jane change video
Tecorders were switched to the extended play recording speed (tape changes required every

6 hours).

The problems experienced with the participating vendor’s equipment during the
second 48-hour test are as follows:

Mikros Systems TEL-2CM - Approximately 3 days of data was lost due to an

error by the test personnel. The unit was not configured to record binned
data after the 48-hour detailed test was complete causing the internal memory
of the unit to fill up. This was not a problem with the classifier, but a setup

error.

Peek GK-6000 - Problems occurred while trying to set up the classifier to
collect binned data. The vendor assisted in the conversion, but the classifier
missed approximately 2 days of data collection. The unit also failed to record
one 30 minute period at the end of one day.

i i - This classifier appeared to
operate correctly during the test, “but the reporting software required to
convert the binary data files into readable text files could not convert the data
files. The problem is still under discussion with the vendor.

TimeMark Delta II - Gaps in the classification data occurred during the
periods of time when the data was being downloaded to a PC. These gaps
were 20 and 11 minutes in length. Most of the last day of data was lost due
to data being corrupted in the memory of the classifier. Attempts were made
to recover the data by the vendor, but they were unsuccessful.

Diamond Traffic Products TI-2001 - An external battery was required to
operate the unit. The battery was installed approximately 8 hours after the
start of the 5-day binning period.

52



Classification of large trucks, especially classes 8 and 9, was very good. Classification
errors were relatively uncommon. Common classification error that did occur included
splitting a class 9 into a class 6 and a class 2, and classification of a class 9 as a class 8
(miscounted axles).

The accuracies of individual classifiers to measure axle spacings for both 48-bour
tests are summarized in Table XL. The magnitude of the mean of the error in measuring
the axle spacings ranged from 0.003 to 0.441 feet (0.4 to 5.3 inches), and the standard
deviation ranged from 0.335 to 2.791 feet. Note that these ranges do not include those
values for the Marksman 660 model, which had considerable errors throughout its data.

. vehi see ange .
Cuestion 4. For those vehicle classification devices that-allow the operator to set_the ional threshold | 7 hicle cl P
i ‘evi jefined | ii ints 1 tf bh 3?

Virtually all of the equipment tested had the ability in some way or another to allow
the operator to adjust the dimensional thresholds between vehicle classes. All of the
equipment tested used the default dimensional thresholds of the classifier except the Mikros
classifier. The Mikros classifier was programmed with the dimensional thresholds known
as Schedule F or the Streeter-Amet Classification Categories ("Field Evaluation of FHWA
Vehicle Classification Categories", Final Report, Technical Paper 84-5, Maine Department
of Transportation, January 1985).

Question 5, How ist ; jefined in th ling points 1 throug!
affected by vehicle speed?

The accuracy of the classification equipment as a function of speed is discussed in
the individual classifier results in Section 5.2. Most of the devices reported vehicle speed
in their output files. The speed calculated by the vendor was used to separate the axle
spacing, wheelbase and overall length measurements into separate speed bins. The mean
and standard deviation of the measurements were calculated for each 5 MPH wide speed
bin over the range of speeds from 30 to 80 MPH. Very few vehicles were recorded with

en wT ce than 20 MAPTT tante

speeds greater than 80 MPH or less than 30 MPH during any of the tests.

The effect of speed on the accuracy of the measurements varied from classifier to
classifier. Typically, the mean error and standard deviation of the error slowly changed as
a function of speed. The direction (towards positive or negative errors) and the magnitude
of the change varied depending on the classifier. The absolute magnitude of the change
was, however, fairly small for all of the classifiers.

175



test site did tend to increase in the mornings and evenings, but there was no heavy mush
hour traffic that could be used to assess performance under extreme traffic conditions.
Therefore, the dependence on traffic volume is not expressly calculated for this study.

ion 10. How is the devi fected by 1 ing devi 2

All of the classification systems tested for this project used some combination of
piezoelectric axle sensors and inductive loops as sensing devices. The combination and
configuration of the sensing devices can possibly have a significant impact on the accuracy
of the classifiers. Two of the vendors (PAT Equipment Corp. and International Road
Dynamics) used two identical classification models with two different sensor configurations.
These provided good points for comparisons of the accuracy as a function of the sensing
device configuration.

The primary difference between the sensing devices used by the individual classifiers
was the number of piezoelectric axle sensors and inductive loops used. Most used 2 axle
sensors and a single loop as the sensing devices. The Peek GK-6000, the TimeMark Delta
Il and the Mitron MSC 3000 DCP classifiers used no inductive loops. The Mikros TEL-
2CM and one configuration of the PAT AVC-100 used a single axle sensor and two
inductive loops. The remaining classifiers used two axle sensors and one inductive loop for
their sensor configuration.

There was no appreciable difference in the classification accuracy between the
equipment using different sensor configurations. Within the set of classifiers using each
particular sensor configuration there was considerable variation in classification accuracy,
but there was no trend or pattern between sensor configurations.

The magnitude of the mean error of the axle spacing measurements for classifiers
using a single piezoelectric axle sensor averaged 0.113 feet, and the standard deviation
averaged 1.144 feet. The magnitude of the mean error for classifiers using two piezoelectric
axle sensors averaged 0.115 feet, and the standard deviation averaged 1.081 feet. The
difference between one and two axle sensor configurations showed no appreciable difference
in these tests. Again, due to considerable errors, the data for the Marksman 660 model was
not included in these calculations.

All but one of the classifiers which measured overall vehicle length used the P-L-P
sensor configuration. Only the Mikros TEL-2CM used the L-P-L configuration. The Mikros
classifier’s overall length measurement errors were near the average for the units using the
P-L-P configuration. Therefore, there was not appreciable difference in overall length
measurement accuracy noted in this project.

181



Table VIII. Accuracy Summary for Peek GK-6000 (Lane 1)

Ast 48-Hour Test
Total
% Trucks
0-20 431 B92
20-40 6.09 BS
40-60 25,62 TL9
60-80 53.57 46.4
Air Temp
50-59 52.59 422 43.1 -0.001 | 1.411
60-69 3.02 86.5 92.4 0.012 | 0.664 *
70-79 4.12 716 922 0.087 | 1.533
80-89 6.11 718 90.4 0.148 | 1.551
Pav Temp
60- 69 31.61 445 45.2 -0.010 | 1.170
70- 79 3.59 84.7 91.7 0.031 | 0.667
80- 89 4.59 78.6 92.8 0.067 {| 1561 *
90- 99 3.59 713 923 0.143 | 2.227
100-109 4.88 71.0 91.6 0.177 | 1.664
110-119 7.00 7113 89.4 0.116 { 0.763

- Does Not

fate Overall Vehicle Length

89



Table XXXI. Accuracy Summary for Golden River Marksman 660
2nd 48-Hour Test

110-119

152

tw Ss oa

a a oe ee ee lee ee eel eee a



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5.2.6 Mitron Systems Corp. MSC-3000 DCP

The Mitron Systems Corp. model MSC-3000 DCP classifier used a P-P sensor
configuration with Autologger MINI axle sensors. The MITRON classifier did not generate
vehicle-by-vehicle records for detailed comparison. It produced only binned records at 15

minute intervals.

The Mitron classifier was included in the first 48-hour test. Piezoelectric axle sensor
failures resulted in Mitron withdrawing its classifier from the project prior to the second
48-hour test and the 7-day test.

The data recorded by the classifier was sent to Mitron Systems for reduction into the
binned data format. The resulting binned data is summarized in Table XVM. The counts
included in the summary are all time periods where both the classifier and the pole camera

are operating without gaps (i.e. gaps caused by tape changes).

ili



IL2 Capacitance (C)

Sensors are made of 2 components:

° Vibracoax piezoelectric cable: 2,600 pF/ft. (8500 pF/m) typical.
[) RG58 extension cable: 33 pF/ft. (110 pF/m) typical.

Standard sensors with 65 feet of extension cable will exhibit:

CL2 (6 ft): about 18nF
CL1 (11.5 ft): about 32nF

A reading lower than 2nF will tell a rupture in the extension cable continuity
(core or screen).

apacitance measurements are valid only on well insulat NSOrs
M3 _ Vi neration Ts

The Vibracoax piezoelectric sensors are generating a voltage when
submitted to a pressure variation.

When installed in the highway pavement, a pressure variation on a sensor
(vehicle passing over, hammer shock, jumping on it) will create a peak
voltage of 30 to 100 mv for less than a second but easily visible on a DC
Voltmeter connected at the end of the extension cable.

CODE: vB 901 D 002 | REV: ©



TIMEMARK INC.

Py P2 P3| pate

9.0"

Figure 13. TimeMark Installation Confii

EQUIPMENT
CABINET

All sensors.
are 6 long



Axles Spacing Statistics Length statistics

Speeds Ween = STD Veh  Axle_spacings Speeds Ween «STD Vehicles

11.359 9.308 3 2 a 3.020 3

0.070 0.000 1 1 30.0-34.9 0.000 1

0.000 0.000 o 0 35.0-39.9 0.000 0

+0.030 0.000 1 4 40.0°44.9 0.000 1

0.038 0.250 wu 7 45.0-49.9 2.395 1%

0.103 0.627 176 2 50.0-34.9 3.907 176

0.108 0.777 541 1043, 55.0-59.9 3.407 541

70.016 0.895 1277) 2265 60.0°64.9 3.931 1277

70.093 0.744 177 2208 65.0-69.9 3.269 1477

70.144 0.550 807 1004 70.0-74.9 4.382 3807

°0.132 0.874 2% 305 %5.0-79.9 4.610 27%

20.616 1.309 6 “0 »60 3.827 “6

-0.022 0.988 4617 Tea? Overall "2.167 4.031 4617

Wheelbase Statistics Length Percentile Statistics

Speeds Ween = STDs“ Vehicles ‘Speeds een STD Vehicles

<30 3.691 3 <0 3

30.0-34, 9.000 1 30.0: 4

35.0-39 0.000 o 33.9 2

40.0-64, 0.000 1 40. 1

45.0-49 0.237 4 45. %

50.0- 0.857 176 50.0- 17%

55.0-59. 1.176 541 55. . 541

60.0-64 1.166 1277 60.0- 1277

65.0- 1.065 477 65.0-69.9 W677

70.0-74 0.739 807 70.0-74.9 807

75.0-79 1,001 2% 75.0-79.9 raf)

>B0 2.098 “6 >80 )

Overall 1.581 4617 Overall 4617

Figure 29. Measurement Accuracy Versus Speed QtPH)
MIKROS TEL-2CM - 2nd 48-Hour Test

=— -_ me

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_ TABLE OF CONTENTS (cont.)

5.2.7 Electronic Control Measure HESTIA ..........--.50006- 113
5.2.7.1 First 48-Hour Test ........-0 20 eee eccrine
5.2.7.2 Second 48-Hour Test
5.2.7.3 Seven-Day Test ....... 0c cece eeu e rer eeeee

5.2.8 TimeMark, Inc. Delta I ...... 0... eee eee eee eee ee eee
5.2.8.1 First 48-Hour Test ...........-
5.2.8.2 Second 48-Hour Test
5.2.8.3 Seven-Day Test ....... 0c cece cece eee eee

5.2.9 International Road Dynamics, Inc. TC/C 530-4D/4P/4L (PR-L-

53) 131
5.2.9.1 First 48-Hour Test .....-....0 eee eee ee eeee 131
5.2.9.2 Second 48-Hour Test ..........-00e eee eeee 135
5.2.9.3 Seven-Day Test .......0 cece eect cece eee 139

5.2.10 International Road Dynamics, Inc. TC/C 530-4D/4P/4L (P-L-
ba
5.2.10.1 First 48-Hour Test ..........-.
5.2.10.2 Second 48-Hour Test ..........
5.2.10.3 Seven-Day Test .......- 2. cece ee eee eee

5.2.11 Golden River Traffic Ltd. Marksman 660
5.2.11.1 First 48-Hour Test 2.00.0... 00: c eee ee eee
5.2.11.2 Second 48-Hour Test ........... 0002s ee eee
5.2.11.3 Seven-Day Test ....... 0. cece eee eee eeee

5.2.12 Diamond Traffic Products TT-2001 (Autologger Maxi) ...... 154
$.2.12.1 First 48-Hour Test .....6-- 02 eee eee cece 154
5.2.12.2 Second 48-Hour Test ........... 002s ee eee 158
5.2.12.3 Seven-Day Test ........ 2. cee cee eens 162

5.2.13 Diamond Traffic Products (Philips Vibracoax) ............+ 163
5.2.13.1 First 48-Hour Test 2.0.0... 2.02 eee e eee eens 163

 9.2.13.2 Second 48-Hour Test .......-.-----++eeeee 167

5.2.13.3 Seven-Day Test .......-. 20. eee e ee eee 171

5.3. CLASSIFICATION ACCURACY VERSUS SENSOR ERRORS .... 172
ANSWERS TO SPECIFIC QUESTIONS .........-.. 00 eeeeee cece 173
AUGMENTED PNEUMATIC TUBE TEST ...............02 see eeeee 183
SUMMARY AND CONCLUSIONS .... 2.0... cence eect teens 185
APPENDIX A oo... cece ce cee ee cee eee enna cee e ene tee enn enn 187
APPENDIX B ... 1... cee ee ce eee eee ete eee net teeeeeee 191





Plezo-Electric:
Data Sheet No. 1

T Golden River Instraments, Inc,
7352 Darttord Drive, #7,
McLean, Virginia 22102

Tel 703 847 5: i
Installation Instructions TM ets: ix 703 047 S648

For TRAFFIC 2000 Slot-Mounted Domed-Profile Traffic Sensors

Handling Precautions

‘The sensors are supplied in a heavy-duty plastic bag which is sealed when the sensor Jeaves our premises.
‘The conients have been cicaned with soivent and are therefore free from any grease or other agent which
might affect its adhesion in the road. You are advised not to open the bag until ready to install the sensor,
and then to keep it clean during handling,

The sensor case is extruded in Ethylene Propylene Diene Monomer, which is not affected by weathering
and is particularly durable and bardwearing. However, reasonable precautions should be taken during
installation not to cut, crush or kink the sensor, as its performance could be affected.

Adhesives and cleaning solvents must be handled with care, and the instructions and precautions given witll ~
those products must be followed.

installation

L If this is a new installation then all the required ducting for electrical connections should
be installed first,

2. The sensor may be supplied in various cross-section widths, from 10mm to 20mm. The
width of the slot to be cut in the road must be 2mm wider than the section to be installed,

end ¢ minimum af dfam deen
and a minimum of 25mm deep.

3. The end ‘of the slot farthest away from the ide of the road should be cut 3mm deeper and
25mm wide for a length of SOmm. This is to allow the free end of the sensor to be pushed
down below the road surface when itis installed. A similar cut-out should be made towards
the other end of the slot, to accommodate the cable end of the sensor. This action is

necessary to avoid having the ends standing proud, where they would be vulnerable to
damage or vandalism,

4. The slot must be blown clean of all loose material and dust, and the surrounding road
surface swept clean.

5. The T2000 Slotmastic adhesive or other suitable adhesive should be mixed according to
instractions, and poured into the slot such that when the sensor is pushed into the slot the
adhesive extrudes along the entire length of the installation, but not excessively,

6. When the sensor is placed into the slot, the extreme end should be pusbed down into the
enlarged hole and held in place with a piece of timber or similar until the adhesive bas gone
off.

7. Similarly push the ‘rat's tail’ end of the sensor down, and hold it down as above.

TRAFFIC 2000 LIMITED
3 Church Terrace, Richmond, Surrey TW10 6SE Page 3
Tel: 0619486736 Fax: 0813320813



5.2.9.2 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number o:
vehicles (real and vendor), mistyped vehicles, sensor errors, exita vendor vi iz
vendor vehicles; correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 56. The classification matrix is presented in both absolute numbers, and

percentages. The classifier correctly classified 72.6% of the vehicles (92.9% if class 2-3

areare mnt inclideda) The number of vehicle axles was miscounte: Val
errors not included). The number of vehicle axles was miscounted 5.35% (percent sensor

errors) of the time. There were less than 0.5% of the vehicles classified that were the result
of a suspected split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 57. The TC/C 530-4D/4P/4L classifier measures axles spacings, wheelbase length,
and overall vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a

function of measured vehicle speed (mph). Note that all measurements are in feet.
Table XXVI contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

135



ELECTRONIC CONTROL MEASURE

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EQUIPMENT
CABINET

/
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Note: Both sensors
are 10'-7.2" long

Figure 11. ECM Installation Configuration Drawing

27



Axles Spacing Statistics
Speeds Mean = 81D

<0 “1.550 0.734
30.0-34.9 6.329 9.248
35.0-39.9 6.697 4.218
40.0-64.9 -0.173 0.609
45.0-49.9 0.028 0.429
50.0-54.9 0.036 0.457
55.0-59.9 0.010 0
60.0-64.9 -0.006 0,
65.0-69.9 -0.013 0.394
70.0-74.9 -0.071 0.
75.0-79.9 -0.372 4

780 0.673 1

Overall 70.014 0.610

135348 921110

Speeds Mean «= STD sVehicles
so 21.550 0.734 4
30.0-34.9 25.318 7.203 5
35.0-39.9 26.790 3.580 2
40.0-44.9 -0.276 0.651 5
45.0-69.9 0.047 0.618 8
50.0-54.9 0.063 0.423 441
55.0-59.9 0.018 0.440 1693
60.0-64.9 -0.010 0.441 4163
65.0-69.9 -0.018 0.393 4481
70.0-74.9 -0.087 0.76% 2037
75.0-79.9 -0.459 1,833 38
>80 +0.87%% 2.620 70
Overall 0.023 0.864 13348
Figure 61.

IRD TC/C 530-4D/4P/4L (P-L-P)

146

Length Statistics

Speeds Mean sTD
<0 71.835 9 1.075
30.0-34.9 34.358 5.226

35.0-39.9 39.695 4.985

40.0-

45.0-4'

50.0-

33.0-5§

60.0-64.9

&.0-69.9

70.0-74.9

%5.0-79.9

>80
Overall +2.152 10.493

Vehicles

Length Percentile Statistics

Speeds Mean $TD
<0 89.04 5.96
30,0-34.9 226.456 34.761
35.0-39.9 276.061 81.253
40.0-44.9 85.133 6.336
45.0-49.9 99.561 53.997
50.0-54.9 100.988 63.026
35.0-59.9 100.075 60.539
60.0-64.9 96.799 52.504
65.0-69.9 92.142 42.962
70.0-74.9 87.761 30.352
75.0-79.9 88.837 36.151

80 87.44 14.08
Overall 94.21 47.9%

Measurement Accuracy Versus Speed (MPH)

2nd 48-Hour Test

Vehicles



truth data was also converted to the standard format. The standard format files were used
as the input for the "Binned” and "Analyze" programs described in the next two sections.

Line Format:
MM-DD-YY__HHMMSS_CC_B VVV.V_LL.LL_AA.AA__X_aa.aa_bb.bb_cc.cc_...
date (month - day - year),

where MM-DD-YY =
HHMMSS = vehicle time where
ae = hour (24 hour clock),
MM = «= minute and
sS = second, .
ce = vehicle class (13 FHWA classes),
B = vehicle subclass,
VvV.V = vehicle speed in MPH,
LL.LL = overall vehicle length in feet,
AA.BA = vehicle wheelbase in feet,
x = number of axles,
aa.aa = axle spacing between axles 1 and 2 in feet,
bb.bb = axle spacing between axles 2 and 3 in feet,
= axle spacing between axles 3 and 4 in feet,

aQ
a
a
-a

Figure 23. The Standard Data Format

The standard data format is shown in Figure 23. Note that not all vendors have all
the information required for the standard format, and the ground truth (or tape) data does
not include vehicle speed. A pound symbol ("#") was used in those fields in the standard
data format for which there was no data. For the case where the data for a particular field
is normally provided by the classifier, but due to an error or other cause is not provided for
a particular vehicle, a dollar symbol ("$") is used as a place holder. Vehicle subclass refers
to the configuration of the axes on the trailer units within a vehicle class. Vehicle subclass
was not used in the analysis of the data for this effort.

4.4 THE "BINNED" PROGRAM

The program “BINNED.c" was written in C, and is designed to transform vehicle-by-
vehicle data files in the standard format to files in which the vehicle classes and axles are
sumuned over a given interval (bin). Typically, the bin size is 15 minutes. The output of the
BINNED program is a file showing the number of vehicles, the number of axles, and the
number of vehicles in each vehicle class for each interval. Also, the program outputs the
percentage of vehicles with greater than 2 axles in each interval and daily summaries.

When run, the program prompts the user for the name of the input file (in the
standard format), the output file name and the time interval over which to bin the data.

58



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Figure 26.



CONTRACT RESEARCH
GDOT RESEARCH PROJECT NO. 9210
FINAL REPORT

\ ot onl ant mY ae, rmMeoa

LN

ACCURACY OF TRAFFIC
MONITORING EQUIPMENT

\ \
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Axles Spacing Statistics

Speeds Mean = STD Veh Axle_Spacings
0.360 1 1
0.000 r) C)
0.067 1 4
0.049 8 24
0.056 52 i
0.006 3130655
0.003 1263-2653
0.009 3049 = 6662
0.007 35096385
9.027 1697 2228
0.016 258 304
0.081 40 40
0.004 10271 19052

Speeds Hean Vehicles
0.360 1

0.000 o

0.270 1

0-46.9 0.066 8
45.0-49.9 0.103 52
50.0-54.9 22012 33
1243

3009

3599

1697

258

40

10271

Figure 39. Measurement Accuracy Versus Speed (MPH)

Peek GK-§000 {Lane 1) - 2nd 48-Hour Test
Peex GR-SC0O0 (Lane 2) 2nd 48-Hour Test

93



5.2.13.2 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 70. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 13.0% of the vehicles (16.2% if class 2-3
errors not included). The number of vehicle axles was miscounted 3.40% (percent sensor
errors) of the time. There were problems involving the recording software for the classifier
during this test. These problems occurred after an upgrade to the software was received
between the first and second 48-hour tests. The problems are associated with the data
recording and not the actual classifying of vehicles.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 71. The TT-2001 classifier measures axles spacings, wheelbase length, and overall
vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed.(mph). Note that all measurements are in feet.

Table XXXVII contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

167



Table XIX. Accuracy Summary for ECM HESTIA

Ast 48-Hour Test

5.78

0.150

20-40 10.41 66.0 85.6 0.112 | 0.708 | 0.585 2270 } 103.01
40-60 UL72 155 85.5 0.128 | 1.064 | 0.666 2351 101.51 | 581
60-80 28.21 69.2 795 0.155 { 1.075 | 2031 2.730 103.87 | 4.92
Air Temp
50-59 57.14 143 28.6 2495 | 3.253 | 12.450 0.0 * 122.13 | 0.0 *
60-69 11.83 76.3 86.1 0.114 | 0.934 | 0.672 2.092 101.62 | 5.33
70-79 4.74 743, 93.0 0.128 | 0335 | 0620 1.200 102.76 | 6.12
80-89 11.83 536 83.8 0.114 | 0832) 0568 2.507 | 103.22 | 9.39
Pav Temp
60- 69 48.48 42.4 515 0.509 | 2.222 | 1225 4.078 100.59 | 9.70
70- 79 9.15 7.3 88.7 0.108 | 0.837 | 0.693 1.980 101.84 | 5.20
80- 89 497 T38 92.7 0.120 | 0.334 | 0.579 1233 | 192.54 | 5.87
90- 99 3.95 TBS 92.9 0.137 | 0.230 | 0.719 1.076 103.29 | 581
100-109 937 623 87.1 0.136 | 0.614 | 0.703 1.440 103.77 | 7.96
110-119 ¥ 3.387 102.74 | 11.40

116

i a2



5.2.10.2 Second 48-Hour Test

‘The classification matrix for the second 48 hour test and the summary of number of vehicles
(real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing vendor
vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 60. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 73.8% of the vehicles (93.9% if class 2-3
errors not included). The number of vehicle axles was miscounted 4.37% (percent sensor
errors) of the time. There were less than 0.5% of the vehicles classified that were the result
of a suspected split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 61. The TC/C 530-4D/4P/4L classifier measures axles spacings, wheelbase length,
and overall vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XXIX contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

144



PREFACE

Under Contract Number 10-9210-50520, Task Order No. 27, the Georgia Department
of Transportation (GaDOT), Office of Materials and Research has tasked the Georgia Tech
Research institute (GTRI) to conduct a Federal Highway Administration (FHWA) funded
study of the accuracy of automatic vehicle classification equipment. The program was
mmonitored by Mr. Rick Deaver of the GaDOT Office of Materials and Research and Mr.
Perry Kent of the FHWA Office of Highway Information Management. Mr. Darrell Elwell
and Mr. Scott Knight of the GaDOT Planning Data Services Bureau provided an
experienced GaDOT road crew under the supervision of Mr. Bob Creasman to perform the
equipment installations described in this report.

This report is authored by the Georgia Tech Research Institute (GTRI) of the

Georgia Institute of Technology. The effort was directed by Dr. Bruce Harvey under the
general supervision of Mr. Eric Barnhart, Chief of Communications and Networking

Division.



Table XL. Accuracy of Axle Spacing Measurements
(All measurements in feet)

Equipment T Model Sensor 48-Hour | Mean Standard
Number Config. Test # Deviation
Mikros TEL-2CM L-P-L 1 0.099 1.113
Systems (Philips) 2 -0.022 0.988
Peek Traffic, | TrafiCOMP P-L-P 1 0.172 0.399
Inc. m (Philips) 2 0.064 0.356
P-P 1 0.110 1.449
GK-6000 (Philips) 2 0.004 0.363
P-P 1 0.098 2.722
(Philips) 2 0.003 0.335
| PAT AVC-100 P-LP 1 N/A N/A
Equipment {Atochem) 2 N/A N/A
Corporation, AVC-100 L-P-L 1 0.078 2.055
Inc. (Philips) 2 0.252 0.420
MITRON MSC-3000 P-P 1 N/A N/A
Systems DCP (Autologger) 2 N/A N/A
Corporation
Electronic HESTIA P-L-P 1 0.120 0.732
Control (ECM) 2 0.441 1519
Measure
TimeMark, Delta 0 P-P 1 0.124 2.791
Inc. (Philips) 2 -0.018 0.419
International TC/C 530- PR-L-PR 1 0.159 0.578
Road 4D/4P/4L (Dynax) 2 0.099 0.515
Dynamics, Inc. P-L-P 1 0.139 0.726
(Philips) 2 -0.014 0.610 |
Golden River Marksman P-L-P 1 N/A N/A
Traffic Ltd. 660 (Traffic) 2 4.625 45.606
Diamond TT-2001 P-L-P 1 0.011 2.340
Traffic (Autologger) 2 0.166 0.978
Products P-L-P 1 0.133 2.124
a 2
le

176

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GOLDEN RIVER TRAFFIC LIMITED
c/o B B K ELECTRONICS INC.
$470 Sacramento Drive
New Port Richey, FL 34655-1619

SALES REPRESENTATIVE
Bob Klaush (813) 376-5661
FAX (813) 372-6918

MODEL NAME
Marksman 660 Classifier

GENERAL DESCRIPTION OF EQUIPMENT
Self-contained multi-lane traffic counter classifier and weighing in motion.
Available for use with loops, tubes, piezo, wim strip and switch inputs.

METHOD OF OPERATION
Stand-alone unit that can be addressed with a computer or via telemetry.

METHOD OF DATA STORAGE
Information not supplied

DATA STORAGE CAPACITY
64K standard, 128K or 1024K can be added.

VEHICLE CLASSIFICATION SCHEME
FHWA 13, 12 speed bins, 6 axle bins, 5 length bins, 4 time bins.

POWER SOURCE
6V 10 APR battery, can be continuously connected to a 12 to 18 Volt AC or
DC power source.

OPERATING TEMPERATURE RANGE
-40°C to 80°C (-40°F to 176°F)

OPERATING VEHICLE SPEED RANGE
5 to 80 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
Outer case: 340 mm x 300 mm x 160 mm deep
Inner case: 250 mm x 145 mm x 190 mm deep
Weight: 8.9 kg and 4.9 kg”

MAXIMUM LENGTH OF LEAD CABLE
Not specified

PURCHASE COST OF EQUIPMENT
$2200 to $3500, depending upon options.

197



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Sddcccddaiagsss

rE SreveceoNegooee x geoeveqerawGone
scodcccsoscgecss

Q eeccDeCeoyoancoe @ eeagececeencocose
Soddodadcgedgia

9

omvommoosmoocoe

g

eomregnegnoaocor

eonneomeormwaccaca

eoerepercacecee

eunwrrercoocc0e
S

&

enneenoeanacd<o
Gddddnddguacozg
ee+0
ecoa

Fancgoaese
idyedcdcorg

eongacanngqocose
ScacadgrodcadcEa

-geqnesaraeccese

adorcrgoecdcdcaza

annaene4eqoeese

Gdudmoddadcccze

goneeneseeeaosa

2nd 48-Hour Test
94

congneercercece Sdépuddcaaeacaa £erogah
ERER3Sc8

ny TBgracemerccece m meanqacennacese
= Rrgsgdcddgdcdad

Classification Matrix for Peek GK-6000 (Lane 2)

N NQQONNOKNGOARCR nw Remawrewnacogasa

‘BR ee
Sa gene eccacedcza

eencercenscacaes we eaaqggnoaqnacacse
eaccoacacaacacaa

¢ 3
eit
iial

3
=
a
g

i

TAmenenaeoransn HN NOeRRoOrAMsN

Sesees

Time interval: 2
1
dmintyped:

5
5
=

Figure 40.



: H ! 1

_ a ee eal ee ee

: ‘ i | i i q

: : ! | | | 1

/ : i , ' 4

am — aa al sem rng a mapa nes ; a
H ; j ! i \ i i |
So
— . ! i

a Pe 0 ra ee ee ee ee ee rere eer wrereren

(seyoul) syyBiep}] sosues

Mikros Axle Sensor Profile
15

Figure 4.



INTERNATIONAL ROAD DYNAMICS, INC.
702 43rd Street
Saskatoon, Saskatchewan
Canada S7K 3T9

SALES REPRESENTATIVE .
Rod Klashinsky (306) 934-6777
FAX (306) 242-5599

MODEL NAME
Traffic Counting/Classifying System - 500 Series
GENERAL DESCRIPTION OF EQUIPMENT
Multi-lane vehicle counter/classifier. Operates in raw data or binning mode,

up to four lanes classification or eight lanes of count. Available with inductive
loops, Dynox axle sensors, piezoelectric sensors, or road tubes.

METHOD OF OPERATION
Unattended, remote access is available with user-supplied modem.

METHOD OF DATA STORAGE
Battery-backed CMOS RAM.

DATA STORAGE CAPACITY
68K standard. Memory can be expanded up to 960K in 128K increments to
allow collection of more raw vehicle data.

VEHICLE CLASSIFICATION SCHEME
Raw data and up to 20 bins.

POWER SOURCE
12 Volt 9-1/2 amp-hr rechargeable battery or optional solar power cell

OPERATING TEMPERATURE RANGE
-40°F to 158°F (Electronics)

OPERATING VEHICLE SPEED RANGE
Dependent upon the sensor being used

DIMENSIONS AND ‘WEIGHT OF EACH MAJOR COMPONENT
12.5" x 9" x 8.25" alum. construction - 25 Ibs

MAXIMUM LENGTH OF LEAD CABLE
200 feet

PURCHASE COST OF EQUIPMENT
$1200 to $2500, depending on the model

199



5.2.13 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table IV. The totals for the

accarac, y; velmcie count and axle count

entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the

first and last full days recorded of the seven days.

Table Iv. Long-Term Count/Classification Accuracy
Mikros Systems TEL-2CK

Total Total
Grad Trath Difference
Vehicles
Axles 65759 57450 8309 114.46 109.02 114.65
Class 1 53 6 47 883.33 700.00 550,00
Class 2 | 13919 14533 614 95.78 91.02 95.04
Class 3 8645, 1168 74aTT 740.15 660.45 989.27
ts 4 75 161 -86. 46.58 59.57 21.54
{ Class 5 _ 671 4263 ~3592 15.74 12.05 25.66
Class 6 196 : 163 33 120.25 125.64 117.89
Class 7 f 2 0 2 - -~- -
Class 8 220 530 -310 4151 45.45 84.87 |
Class 9 3073 2679 394 114.71 110.12 116.27 |
Class 10 27 140 13 19.29 18.60 23.81 +
Class11# 88 69 19 127.54 117.24 129.41
Class 12 | 26 0 26 ~ - - |
Class 13 0 5 5 0.00 0.00 0.00
L Class 15 L ay o ° a - es }
74

—- kp fe Oh ah Se oe im a an

_— = oa

—_- am i Ge



8 SUMMARY AND CONCLUSIONS

The classification accuracies resulting from this test ranged from 63.5% to 79.1%.
The most common errors occurred between Class 2 (passenger vehicles) and Class 3 (other
2-axle, 4-tire vehicles). A small pickup truck (class 3) is very difficult to distinguish from a
large car (class 2) based on length and axle spacing. If class 2 and 3 are combined, then the
classification accuracies ranged from 78.8% to 96.2%.

Temperature of the air and pavement was found to have little effect on the
performance of the classifiers. However, the range of temperatures was somewhat limited
for this test. The percentage of trucks (vehicles with more than 2 axles) tended to have
some effect on the classifier accuracies. The classification of class 9 vehicles (a majority of
the trucks) was very good on most classifiers, and hence the classification accuracy tended
to improve as the percentage of trucks increased. The longer vehicle lengths and axles

spacings did result in greater measurement errors as the percentage of trucks increased.

Precipitation, although expected during the second 48-hour test and the 7-day test,
did not occur during any of the tests. Therefore, no results concerning the performance of
these devices in rain was obtained.

The sensor configuration used by the classifiers did not appear to have a significant
effect on the accuracy. Classification accuracy, axle spacing measurement errors, and overall

length measurement errors appeared to be independent on the sensor configurations. The
primary factor observed in this test to affect the classification accuracy was the performance

of the axle sensors. The ability of the equipment to accurately classify vehicles was linearly
dependent on the ability of the sensor and classifier to accurately count the number of axles.
Therefore, performance of the piezoelectric axle sensor and the interface electronics in the
classification equipment are the primary factors effecting the accuracy of the equipment.

A further opportunity has arisen to collect more data concerning the performance of
these classification equipments. Road construction is under way at the test site and will
result in the sensors in the roadway being overlaid as part of a widening of the road. This
presents an opportunity to test the performance of the devices after a pavement overlay.
This issue is important to the maintainability of a traffic monitoring site. The results of the
overlay tests will be reported in and addendum to this report.

The augmented tube test performed in parallel with the second 48-hour test was
essentially unsuccessful. The Peek TrafiCOMP III was incorrectly programmed resulting in
the data from the two lanes monitored being summed into one record and no individual
lanes being recorded: While there is some possibility that limited results can be obtained
from the single data file, there will be much greater potential for analysis if the test is
repeated. Therefore, a repeat of the augmented tube test is planned in conjunction with the
overlay tests. These tests should be conducted in time for the results to be included in the

final report.

185



i? > a a

Table II. Accuracy Summary for Mikros Systems TEL~2CM
lst 48-Hour Test

Axle | Axe
Mean | S.D.
40-60 14.86 716 86.8 0.091 | 0.672 | 2679 | 2027 5.684 |
60-80 12.09 78.0 835 0.129 | 0.634 | 3.351 1.990 5.838 ff
Air Temp
50-59 14.87 66.9 83.7 0.117 | 0.767 | 2.172 2.418 108.84 | 26.77
60-69 15.45 NZ 82.6 G.115 | 0.985 | 2.403 2.916 108.34 } 29.81
78-79 13.14 72.7 83,1 0.101 | 1.322; 2140 2.864 33.04
80-89 13.25 70.1 815 0.080 | 1.181 | 1.918 2.240 20.61 i
Pav Temp .
60- 69 13.63 69.8 84.6 0.084 | 0512 | 2421 1.906 { 10832 | 6.63
70- ww) 1594 106 $26 0112 9.992 2342 2.965 108.40 3153
80- 89 12.83 726 83.1
90- 99 11.78 TLS 818
100-109 1238 72.9 83.9
110-119



Be ee ee oe

Figure 55.
Figure 56.
Figure 57.
Figure 58.
Figure 59.
Figure 60.
Figure 61.
Figure 62.
Figure 63.
Figure 64.
Figure 65.
Figure 66.
Figure 67.
Figure 68.
Figure 69.
Figure 70.
Figure 71.
Figure 72.

LIST OF FIGURES (cont.)

Measurement Accuracy Versus Speed (MPH) .......-.---+ 000s 133

IRD TC/C 530-4D/4P/4L (PR-L-PR) - 1st 48-Hour Test

Classification Matrix for IRD TC/C 530-4D/4P/4L .....-...-.--- 136
(PR-L-PR) 2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .........--.0000ee 137
IRD TC/C 530-4D/4P/4L (PR-L-PR) - 2nd 48-Hour Test

Classification Matrix for IRD TC/C 530-4D/4P/4L .....---- +--+ - 141
(@P-L-P) ist 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .......-.-+--+--5> 142
IRD TC/C 530-4D/4P/4L (P-L-P) - ist 48-Hour Test

Classification Matrix for IRD TC/C 530-4D/4P/4L_ .......-...+-. 145
@-L-P) 2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........-----+---- 146
IRD TC/C 530-4D/4P/4L (P-L-P) ~ 2nd 48-Hour Test

Classification Matrix for Golden River Marksman 660 ............ 150
2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH). ........- Vek e eens 151
Golden River Marksman 660 - 2nd 48-Hour Test

Classification Matrix for Diamond TT-2001 ...........-..-2005- 155
(Autologger) 1st 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ..........-..-005- 156
Diamond TT-2001 (Autologger) - 1st 48-Hour Test

Classification Matrix for Diamond TT-2001 ...........-..0--00- 159
(Autologger) 2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .........+.-0-eeee 160
Diamond TT-2001 (Autologger) - 2nd 48-Hour Test

Classification Matrix for Diamond TT-2001 ...........-.--.-0-- 164
(Philips) ist 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........----+-05-- 165
Diamond TT-2001 (Philips) - 1st 48-Hour Test

Classification Matrix for Diamond TT-2001 ...........--.eseeee 168
(Philips) 2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........-----0--0+ 169
Diamond TT-2001 (Philips) - 2nd 48-Hour Test

Classification Accuracy Versus Sensor Errors .........-+---+.+--5 172

XV



APPENDIX B
EQUIPMENT BRIEFING FORMS
191



2.3.9 Diamond Traffic Products

Diamond installed a model 2001 multi-lane classification unit with two sets of sensors
configured as two lanes. The sensor layout is shown in Figure 19. The first sensor
configuration uses two Autologger-Gates, piezo cable, class 2, Maxi replaceable flush fitting
design axle sensors and one three-turn loop. The axle sensors consist of channels which are
epoxied into the road and replaceable sensor elements. The channel has 3/4" plastic tubing
is attached to form a conduit from the channel to the edge of pavement for the coax cable.
The second sensor configuration uses two Philips piezoelectric axle sensors one three-turn
loop. The rutting at the location of axle sensors 1 through 4 was 4/32, 5/32, 5/32, and 6/32,
respectively. Installation began on 1/19/93 and was finished on 1/29/93.

The slots for the Philips were cut on the morning of 1/19/93, but because of rain that
began around noon, the installation could not be completed, The slots were filled with sand
until the weather cleared and the installation crew could be rescheduled. On 1/26/93 (49°
F and partly cloudy) the slots were cleaned then dried and preheated with torpedo heaters.
There was no pavement cracking or other noticeable effects on the slot after the seven day
delay. Two layers of duct tape were used along the top of the slot. The sensor had five
leveling plates installed with tie wraps. The epoxy used was E-Bond G-100. Enough epoxy
was poured such that excess material extrudes around the sensor then the excess was
trowelled off and smoothed using a putty knife. Weights were placed on the leveling plates
and the epoxy was cured using the torpedo heaters.

The Autologger channel was installed much like a typical piezoelectric sensor, and
the general axle sensor installation procedures were followed with some extra steps. On
1/27/93 (58° F and clear), the slots were cut and cleaned then dried and preheated with
torpedo heaters. Two layers of duct tape was used along the top of the slot. A strip of duct

tape was also used on the top of channel to keep epoxy out. The epoxy used was E-Bond

G-100. The channels were installed using eight tie-wrapped leveling plates, and since the
channels were slightly flexible, good conformity to the rutting profile was achieved. Before
installation, the channels were thoroughly cleaned with acetone for better epoxy adhesion.
Sufficient epoxy was poured in the slot such that it extruded out when the channel was
placed in the slot and seated. The excess epoxy was removed and the surface was then
smoothed with a putty knife. The epoxy was allowed to cure under ambient conditions. On
1/29/93 (61° F and partly cloudy), the protective tape was removed, the channel was
thoroughly cleaned of any debris, and the sensor element was installed using the same
procedure as for the mini-replaceable (Section 3.3, MITRON).

All axle sensors were tested with an oscilloscope and were working properly. The
loops measured 152 microhenries for the Autologger configuration and 154 microhenries for
the Philips configuration; both loops demonstrated good frequency stability. The sensor
profile in Figure 20 shows that all four sensors conform well to the road surface with the
maximum height variation of 0.1 inches. The lowest point is -0.08 inches.

39



Axles Spacing Statistics

Hean sTD Veh

<0 4.659 16

30.0-34.9 5.095 6

35.0-39.9 7.993 16

40.0-44.9 3.650 B

43.0-49.9 2.071 oo

50.0-54.9 0.938 383

55.0-59.9 5.640 1515

60.0-64.9 0.460 3749

65.0-69.9 0.577 3895

70.0-74.9 1.434 1798

75.0-79.9 1.669 669

>80 3.481 173

‘Overall 0.011 2.340 = 12103

Wheelbase Statistics

Speeds ean sTD Vehicles

30 2.559 8.595 16

2344 6

288 16

26% 23

+268 60

517 383

BBS 1515

660 3749

836 3895,

405 1798

479 469

928 are)

-773 12103

Figure 65.

Diamond TT-2001 (Autologger)

Axle_Specings

22
5
38
33
139
852
3164
7922
6716
2625
589

212
22147

Statistics

Mean sD
4.239 25..
22.640 16..
13.127 22.

328
25
179
835
61

Vehicles

Length Percentile Statistics

Speeds Mean STD
30 247.63 212.66

30.0-34.9 318.294 264.479

3 lj

5

50.

55.

60,

6

70.0-74.9 93.072 31.101

75.0-79.9 89.697 17.570
80 106.16 133.96

Overall = 97.62 45.35

Measurement Accuracy Versus Speed (MPH)

rv

A

ist 48-Hour Test

Vehicles

i oa oo he owt ee oo ee ho oa



axles Spacing Statistics
Axte_Spacings

eeeesiagy.u. F

064 0.356 12020 20296

‘Speeds Wesn = STD) Vehicles
<30 0.000 0.000 1
30.0-34.9 -0.067 0.178 3
35.0-39.9 0.130 0.218 4
40.0-44.9 0.087 0.221 2B
45.0-49.9 0.192 0.332 107
50.0-54.9 0.146 0.277 530
55.0-59.9 0.141 0.318 1719
60.0-64.9 0.125 0.319 &747
$5.0-69.9 0.077 0.263 3300
70.0-74.9 0.069 0.238 1264
75.0-79.9 0.098 0,191 298

>B0 0.113 0.217 rs
‘Overall 0.109 0.293 12020

Figure 33. Measurement Accuracy Versus Speed (MPH)
Peek TraficomMP III - 2nd 48-Hour Test

81



Table XXXVII. Accuracy Summary for Diamond TT-2001
(@hilips) 2nd 48-Hour Test

Air Temp
60-69
10-79
80-89

Pav Temp
60- 69
70-79
80- 89
90- 99
100-109
110-119

170



INTERNATIONAL ROAD DYNAMICS INC.

CORPORATE OFFICE: 702 48rd Street East, Saskatoon, Saskatchewan, CANADA 87K STO
Telephone: (306) 653-6600 Facsimile: (306) 242-5599

TEMPERATURE:

<55 <13 3x 33g - 10 kg (6 ql) Pall
Sxi7g- Skg (3 qv Pail
56-75 14-24 2x 33g - 10 kg (6 qt) Pail
2xi7g- Skg (3 ql Pail
>75 >25 1x 33g - 10 kg (6 qt) Pall

1x17g- Skg (3 ql) Pall

* Electric drill

© Mixing paddle for drill
* Grout and BPO

© Well ventilated space

a) Open pail and start mixing using the drill and mixing paddle.
Mix until all fine aggregate al the bottom of the pail is thoroughly
mixed in and the grout takes on a smooth texture (no lumps).

b) Add appropriate BPO as indicated in “Directions For Use”.
¢) Mix thoroughly for an additional 2 minutes.

) Apply grout - (10-50 minutes working time). Ensure no voids or
air bubbles become trapped in the grout - (45-60 minutes cure).

¢) Traffic may be allowed to pass after surface is tack free.

«26 SncDoe Specs



Piezo-Electric
Data Sheet No. 2

al Golden River Instruments, lnc,
7352 Dartford Drive, #7,
McLean, Virginia 22102
Tel 703 uh? b0U6 ux 703 847 5648
Plezo-electric Sensors - Performance Data

graphite polyurethane jacket

‘The heart of the sensor cable is a layer of piezo-electric polymer which gencrates a charge when subjected
to changing stress. Thus the cable produces an electrical signal in response to vibration, impact or pressure.
Amplitude of the output depends on the intensity of the impact, and frequency is determined by the speed.

TRAFFIC 2000 cable is a very tough and durable transducer with tightly-controlled mechanical and
electrical properties. It is supplied embedded in 2 variety of high-performance rubber profiles, each
carefully designed to match the cable characteristics to the particular duty required, Please refer to other
Data Sheets in this series for design and application information.

‘Typical piezo-electric cable characteristic

19000 ‘Charge output as a function of pressure
12000
31900 vA
10000
9000
pe
8000 2
va
7000
6000
000
4000
3000
ve

2000 <1
1000 +

°

0 2 «0 oo a 100
pressure (bar)
—~ Best ft © Pewdate

TRAFFIC 2000 LIMITED
3 Church Terroce, Richmond, Surrey TW10 6SE
Tel: 0819486736 Fox: 0813320813



Time interval: 2

WwW 12°23 «4 15

10

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Saddacsemngss ta

eaqesaqe<~amace<e
Saodcddcdasrsadasa

erqnenehhmroosyt

SOMAAI*<VQhngo<d
docdncagaancasg
eecanessescens
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ewnngnarn acces]
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eenyausneagesse
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grddcridcdddaze

TAME MOR OOOCAM

Wextra Vend:

Missing Vend:

Correct

splits:

36

#Combinat fons:

ification Matrix for Diamond TT-2001

155

be ee oe | a



Tools - Equipment

This is a non exhaustive list of tools and equipment needed for the Vibracoax sensors
installation in road pavements (either asphalt or concrete): .

Traffic Control Signs
- Paint to mark pavement, rulers, strings

- Diamond blade saw

- Chisel and hammer

- Compressed air, hose

- Hot air generator or gas burner

- Temperature probe

- Duck tape

- Generator

- Electric drill with mixer paddies

Latex rubber or leather gloves, safety glasses

Vibracoax Sensors

The appended figures describe the standard Vibracoax Piezoelectric Sensors:

- Class 1, for Weigh In Motion, 11.5 ft long
- Class 2, for classification, 6 ft long

The sensitive piezoelectric sensors are encapsulated inside a protective aluminum
channel 1" high 1 1/2" wide, 4" longer than the sensor. The aluminum channel! has
lips on the bottom to ensure a perfect anchoring inside the pavement.

The encapsulation compound is either a sand epoxy or a hard polyurethane F80. This
assembly can survive exposure to temperature up to 200F for half an hour without
damage. The sensor is connected to a 50 ohms Coaxial cable. The outer sleeve is
made of PVC, the inner insulation being polyethylene. The maximum temperature the
coaxial cable can survive is 170F. To protect the coaxial cable while transportation
and installation, the first 3" of the cable outside the sensor are surrounded by a plastic
tubing. Sensors must be electrically checked prior to and after the installation (see
procedure VB 901 D 002) procedure.

AUTHOR: GB PAGE: 2/5
CODE: VB 901 D 003 REV: ‘O

THERMOCOAX NORCROSS

F1002



between the vendor vehicle and the ground truth vehicle, the program searches for splits and
combinations of vehicles. If no splits or combinations are found then the program declares
this a Sensor Error. The misclassification is recorded, but no length or axle spacings
measurements are used in the statistics for the device. Only a match in time and number
of axles is used in calculating the length and axle spacing statistics.

When ANALYZE is run, the user is prompted to enter the “Real” (ground truth)
data file name and the “Vendor” (classifier) data file name. These files are expected to be
in the standard format. The program then prompts the user to enter the start time for the
analysis (must be in the starting day of the ground truth data). Finally, the user is asked to
enter the "Time Interval" (maximum time differential).

The outputs of ANALYZE are the following seven files:

TABLE.OUT - The file containing a classification matrix depicting the classification
accuracy of the vendor classifier. It also contains the mean and
standard deviation of the vehicle length, wheelbase and axle spacing
Measurements as a function of the speed of the vehicle.

MAIN.OUT - The file contains the vehicle data from the ground truth and the
vendor data files for every vehicle which was not matched in time and

number of axles.

EXTRAV.OUT - This file contains the data from the ground truth vehicles for which
there were no matching vehicle in the vendor data file.

MISSINGV.OUT - This file contains data from the vendor vehicle for which there were
no matching vehicle in the ground truth data file.

SENSORER.OUT- This file contains the vehicle data from the vendor and ground truth
data files for vehicles which matched in time, but had different number

of axles (declared a Sensor Error). _

MISTYPED.OUT - This file contains the vehicle data from the vendor and ground truth
data files for vehicles which matched in time and number of axles, but

had different classifications.

SPLT-CMB.OUT - This file contains the vehicle data from the vendor and ground truth
data files for vehicles which the vendor classifier either split into two
vehicles, or combined two vehicles into one.

The TABLE.OUT file contains the primary results of the ANALYZE program. The other

files, particularly SPLT-CMB.OUT, are used to check the classification errors detected by
the program for accuracy. Certain combinations of lane changes, sensor errors, and dense

60



j

—_

©
T
aN

fTM

Extra

ya

od

ory >

NSH

os.

Missing
vro—o( ees)



INSTALLATION COST
Varies with users desire for enclosures and type of sensors

NOMINAL INSTALLATION TIME
5 to 10 minutes

INSTALLATION PROCEDURE

Attach sensors, program study to be conducted

SOME STATES CURRENTLY USING THIS EQUIPMENT

Arizona. Wknois. Flo: North Carolina, South Carolina
Arizona, Hlinois, Florida, North ‘cuna, Si

OTHER COMMENTS

Piezo unit has multiple threshold adjustments for use with any sensor. New

model performs 16 lanes of volume, 8 lanes speed/classification.

GTRI COMMENTS
Piezo-Piezo.

204



Sensor Heights (inches)

PAT EQUIPMENT CORPORATION, INC.
0.15 f
0.10 F-~—4
0.05 Fi
0.00 |

o
Oo
a

0.10 f
0.15 §
0.20 £ x4
0.25 |
0.30
0.35

2 3 4 5 6
Distance from Solid Line (feet)

Figure 8. PAT Axle Sensor Profiles

21



Table XXXVL Accuracy Summary for Diamond TT-2001

Philips) 1st 48-Hour Test

Pav Temp
60- 69
70-79
80- 89
90- 99
100-109
110-119

0.604 | 9.789
0.138 | 0.643
0.139 | 0.566
O.115 { 0.287
0.124 | 0.254

0.148
1.286
-1218
-1.306
-1.216

[un

3.123
1.565
1.611
2.830

94.75

95.14 | 1633
94.49 6.24
94.41 8.09
94.83 | 11.46
a)

166



of 300’. This cable should have an outer shield for additional lightning
protection. The loop wires are extended with 2 #16 shielded cables and a
splice kit.

PURCHASE COST OF EQUIPMENT
- Depending on quantity and memory capacity, $2200 to $4300

INSTALLATION COST
Depending on location, lane closure requirements, weather, number of lanes
and systems, installation costs can vary from $1500 to $8000 per lane

NOMINAL INSTALLATION TIME
Installation of 2 sensors in one lane takes approximately 4 hours for the
permanent sensors.

INSTALLATION PROCEDURE
Install permanent induction loops and permanent piezo axle detectors, lay
conduits, cabinet base concrete and pullboxes as required, power and phone
line connection.

SOME STATES CURRENTLY USING THIS EQUIPMENT
Alaska, Florida, North Carolina
OTHER COMMENTS
System upgradable to WIM; other electronics for WIM available:
- DAW 100 Bending Plate, permanent
- DAW 190P Portable for Piezo, capacitance mat and

bending plate.
bending plate.
GTRI COMMENTS

Pat will be testing two sensor configurations, one with a Piezo-Loop-Piezo and
the other with a Loop-Piezo-Loop.

206



Figure 16 shows fairly good conformity to the road surface with the highest point at 0.09
inches and the lowest at -0.05 inches. ,

On initial system installation and checkout on 1/18/93, the classifier would not
recognize the DYNAX sensors. The IRD representative found a loose connector inside the
classifier, and after repairing it, the classifier worked well with the Dynax sensors. As a
normal part of setting up a new installation, the sensitivity of the piezoelectric sensor circuits
were adjusted internally for optimum detection.

Sensor number three started to break out of pavement after approximately one
month. The epoxy was chipping away at the end of the sensor and in the wheel path. IRD
patched the sensor by making saw cuts along the chipping areas, removing the loose epoxy,
and applying more epoxy of the same type. The epoxy failure may have been because of
the difficulty encountered with its installation as discussed above. After the repair of the
sensor, the system was rechecked and readjusted for optimum performance. The classifier
was then approved by the vendor for testing.

33



5.2.5 PAT Equipment Corporation, Inc. AVC-100 (L-P-L)

The second PAT Equipment Corporation, Inc. mode AVC-100 classifier used an
L-P-L sensor configuration with Philips Vibracoax axle sensors. The AVC-100 used for the
second (L-P-L) configuration did not have sufficient memory to store vehicle-by-vehicle
records for the testing periods. Therefore, the data was recorded by a portable computer
via the serial port on the classifier. No conversion was necessary and thus data reduction
was accomplished for the second PAT configuration.

5.25.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 42. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 76.6% of the vehicles (95.0% if class 2-3
errors not included). The number of vehicle axles was miscounted 1.49% (percent sensor
errors) of the time. Less than 1.0% of the vehicles classified were the result of a suspected
split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 43. The PAT classifier measures axles spacings and wheelbase length. The
measurement error statistics (mean and deviation) for all measurements are included in the
figure as a function of measured vehicle speed (mph). Note that all measurements are in
feet.

Table XV contains a summary of the results of the classification accuracy as a
function of percent vehicles with greater than two axles, air temperature and pavement

temperature.

102

—_— ome Ow ee ee le oe oe



Sensor Heights (inches)

GOLDEN RIVER TRAFFIC LIMITED

0.15 f
0.10 | fA Nes
0.05 }/--!
0.00 t |

0.05 |
0.10. |

0.15
-0.20
-0.25
0.30
0.35

|
|

_ el _

oi]:

Fare Serer eres oer erase rere

0

2

|
|
or
vara erarere waver
1

3.4

6 7 8 9

Distance from Solid Line (feet)

Figure 18.

GRI Axle Sensor Profiles

38



PEEK TRAFFIC, INC.

1500 North Washington Blvd.

Sarasota, FL 34236

TIMEMARK, INC.
P.O. Box 12947
Salem, OR 97309

190

Jim Stemitz (813) 366-8770

FAX (813)365-0837

TrafiCOMP III and GK-6000
Classifiers

Dan Gossack (503) 363-2012
FAX (503)363-1716
Delta II Classifier



Time interval: 2

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31

‘#Combinations:

Classification Matrix for TimeMark Delta II

Figure 50.

ist 48-Hour Test



INTERNATIONAL ROAD DYNAMICS, INC.

650"

was tr wee
= _——— = —
- F Tar SAT c+
' [e " 1 ° 12 t eT ‘

Te c T

t Core | iL |
| |
1 |

Na

90"

\
a a
oT
|
|

EQUIPMENT
CABINET

Note: The first two sensors
hove lengths of 7'-4.8",
ond the last two sensors
have lengths of 7°

Figure 15. IRD Installation Configuration Drawing

24
a

a me om ee ee i



MIKROS SYSTEMS
P.O. Box/POSBUS 20309
ALKATRANT 0005
SOUTH AFRICA

SALES REPRESENTATIVE
Joban Steyn +27 12 73 1010
FAX +27 12 73 4646

MODEL NAME
TEL-2CM Traffic Event Logger

GENERAL DESCRIPTION OF EQUIPMENT °
Multi-lane vehicle classifier. Operates in raw data or binning mode. Available
with inductive loops, piezoelectric sensors, or road tubes. Also available with
capacitance weigh mats.

METHOD OF OPERATION
Unattended, capability to access data via telemetry is standard.

METHOD OF DATA STORAGE
Non-volatile memory.

DATA STORAGE CAPACITY
32K, expandable to 8M.

VEHICLE CLASSIFICATION SCHEME
Raw data and up to 15 bins. FHWA scheme F selectable.

POWER SOURCE
12 V sealed lead-acid battery (will operate 12 days from a fully charged,
24 A-h battery). Optional solar panel.

OPERATING TEMPERATURE RANGE
Sensors: -20°F to 140°F
Electronics: 0°F to 140°F

OPERATING VEHICLE SPEED RANGE
3 to 100 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
13.8" x 10.0" x 10.2" alum. casing - 26.5 Ibs

MAXIMUM LENGTH OF LEAD CABLE
400 feet

PURCHASE COST OF EQUIPMENT
$2500 to $3500

201



ELECTRONIC CONTROL MEASURE
P.O. Box 888
Manor, TX 78653

SALES REPRESENTATIVE
Ron White (512) 272-4346
FAX (512) 272-5161

MODEL NAME
HESTIA Classifier

GENERAL DESCRIPTION OF EQUIPMENT
Card/rack mounted portable or permanent classification and counting system.
CMOS component-based electronics for low power consumption at 12 Volts
DC. Collects classification and count data in up to 8 lanes of traffic. Collects
both individual vehicle data and/or binned data. Available with piezoelectric
sensors and/or inductive loops.

METHOD OF OPERATION
Unattended operation with data access via telemetry. Piezo detector is fully
automated to allow reliable operation with variable sensor sensitivity.

METHOD OF DATA STORAGE
Binned and/or individual vehicle storage

DATA STORAGE CAPACITY
8M

VEHICLE CLASSIFICATION SCHEME
User programmable (default FHWA scheme F) with up to 56 vehicle
configurations.

POWER SOURCE
12V DC

OPERATING TEMPERATURE RANGE
-40°F to 176°F

OPERATING VEHICLE SPEED RANGE
10 to 120 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
6" x 8" x 12"; 15 Ibs

MAXIMUM LENGTH OF LEAD CABLE
Loop: 900 feet
Piezo: 600 feet

195



INSTALLATION COST .
- Varies with users desire for enclosures and type of sensors

NOMINAL INSTALLATION TIME
5 to 15 minutes

INSTALLATION PROCEDURE
Attach sensors to termination box and select a typical small vehicle. The
system will perform automatic calibration.

SOME STATES CURRENILY USING THIS EQUIPMENT
West Virginia

OTHER COMMENTS ,
The TEL-2CM can be fitted with a weigh interface to collect axle and total
weight data with either piezo or capacitance weight sensors. The PC-based
software TELCOM allows the user to either directly or remotely via a
modem, view live traffic information, extract data, detect violations and
monitor the diagnostic features of the system.

Local USA agent: I.D.C.
P.O. Box 5397
Long Beach, CA 90805
Fax: (813) 789-0568

GTRI COMMENTS
Loop-Piezo-Loop



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Table III. Accuracy Summary for Mikros Systems TEL-2CM
2nd 48-Hour Test

0-20 4.06 62.7 78.7 0.002 | 0.995 | -2.277 | 3.872 90.46 | 27.95
20-40 7162 652 BS 0.065 | 0.999 | -1.837 | 4.524 93.77 | 29.97
40-60 0.00 9 84.6 0.116 { 0.432 | -0.717 1.594 98.09 } 06.09

60-69 2.32 66.5 80.4 0.033 | 0.887 | -1.955 3.925 92.72 | 29.24
10-79 730 605 77.0 0.024 | 1.020 | -2305 4.156 90.29 | 24.36
RO-89 1.62 65.7 81.2 0.046 1.400 -2,392 3.710 90.22 42.90

60- 69 00.83 67.6 9.5 0.049 | 1.023 | -1.28 4.332 96.63 | 42.44
70-79 03.50 673 815 0.028 | 1.014 | -2.004 4.652 92.95 | 30.77
80- 89 08.63 60.9 TI 0.003 | 0.857} -2.441 4.193 89.99 | 18.38
90- 99 12,46 53.9 B36 0.025 | 1.263 | -2.719 3613 87.83 | 13.33
100-109 05.21 623 782 0.033 | 0.605 | -2.362 3.008 89.09 | 12.03
110-119 00.96 65.2 199 0.011 | 1.034 | -2502 3.389 88.87 | 29.16

ee ee a en

73



Sensor Heights (inches)

LECTRONIC CONTROL MEASURE

0.15

ek
0.05

0.00 +
0.05 |

0.10 ~~:
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Figure 12.

ECM Axle Sensor Profiles

28

8

9



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ist 48-Hour Test

Figure 46.

114



5.2.33

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Tables XII and XII for lanes 1
and 2, respectively. The totals for the entire seven days for the vendor and classifier are
listed. Also, the difference (ground truth minus vendor) and the percent difference (ground
truth * 100 / classifier) are listed. To assess the change inaccuracy over the seven days, the

Seven-Day Test

percent difference is calculated for the first and last of the seven days.

Table XII. Long-Term Count/Classification Accuracy
Peek GK-6000 (Lane 1)

Total Total Total Total Ist Day Last Day

Grod Truth | Classifier Difference Percent Percent Percent
Vehicles 44841 32872 11969 136.41 144.59 12137
Axles 118765 N/A N/A N/A 134.04 N/A
Class 1 58 10 48 580.00 433.33 400.00
Class 2 20744 16769 3975 123.70 130.28 118.99
Class 3 12746 4110 8636 310.12 30737 275.70
Class 4 87 278 -191 31.29 25.00 25.00
Class 5 1399 1006 393 139.07 82.00 139.44
Class 6 589 504 85 116.87 103.77 105.98
Class 7 6 42 -36 14.29 40.00 12.50
Class 8 tH 735 742 -7 99.06 98.60 96.53
|_Class 9 8101 7093 1008 114.21 108.23 102.78
Class 10 96 61 35 15738 155.56 130.77
Class 11 215 180 35 119.44 104,76 104.65
I Class Rn 65 67 2 97.01 92.86 92.86
Class 13 0 29 -29 0.00 0.00 0.00
Class 15 oO 1981 -1981 0.00 _ 0.00

98



Page 6
CARDBOARD ON PUT HEATER AT
AIRFLOW 4/ \ 0 OF TUNNEL
EPOXY
SENSOR 7

Nags p
AR Weer
Rar gr, RA RAY

D

ges are ag ‘ngs a
par - “PA?
RE REEL Rees

Figure 13: A cardboard "tent can be used

to speed up the curing times if heaters are
used

the slot.

Clean up the area once the epoxy has hardened. The
hardening time for the epoxy will vary based on
temperature, humidity and type of epoxy used. NO
TRAFFIC SHOULD BE ALLOWED TO PASS OVER

THE SENSORS UNTIL THE EPOXY JIS FULLY

BARDENED!
HARDENED!

If the sensor was mounted flush with the road and higher
signals are desired, a piece of asphaltic adhesive tape

know as bituthane or polyeuard may be placed over the
oituthane or po. uyguars may 0

sensor (Figure 14) to increase the signal level. This tape
will give you increased
signal levels, additional
sensor protection, and, if
a snowplow tears off the
tape, it can be replaced. {- SENSOR
The disadvantages of

BITUTHANE/POLYGUARD TAPE =
HARDENED EPOXY

using the tape is that it can only be applied under certain

conditions, ‘and that the signal may have. to be monitored to
ensure uniform levels as the tape wears. Contact Elf Atochem
Sensors, Inc. if you have any questions.

You are now complete. Once the epoxy has fully hardened, the
lane of traffic can be again opened. The electronics needs to be
connected, and you are ready to start classifying vehicles. The
majority of sensor failures are caused by damage to the lead wire
causing water penetration, and improper mounting of the sensor -
especially in the use of improper epoxy and allowing traffic to

pass over before the epoxy has fully hardened. Please follow all the above procedures and if
you have any questions, please call - ELF ATOCHEM SENSORS, Inc. is committed to total

customer satisfaction.

Figure 14: Polyguard tape
placed on top of the flush

mounted sensor will increase the

output level

Elif Atochem Sensors Inc, PO Box 799, Valley Forge, PA 19482 # (215) 666-3500 Fax (215) 666-3509



Time interval: 2

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Classification Matrix for PAT AVC-100 (L-P-L)

Figure 44.

2nd 48~-Hour Test

107



PURCHASE COST OF EQUIPMENT
$3000 to $6000

INSTALLATION COST
Variable depending on permanent or portable installation

NOMINAL INSTALLATION TIME
Permanent: 3 hours/lane; portable: 5 - 20 minutes

INSTALLATION PROCEDURE
Attach sensors, use computer to set up study

SOME STATES CURRENILY USING THIS EQUIPMENT
Information not available

196



Table XVII. Binned Count/Classification Accuracy
Mitron MSC-3000 DCP - 1st 48-Hour Test

Class 1

|
14 26

Class 2 6851 9702 2851 7061

Class 3 4493 1993 2500 225.44

Class 4 | 2 117 55 52.99

Class 5 628 581 4 108.09

Class 6 410 420 10 9762 |
Class 7 0 0 0 i
Class 8 264 361 91 73.13

Class 9 | 2987 3100 “13 96.35

Class 10 31 B 8 134.78

Class 11 89 101 2 88.12 |
Class 12 25 28 3 89.29

Class 13 + 0 9 9 0.00

Class 15 32 0 32 -

112



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219



INSTALLATION COST
Varies with users desire for type of sensors.

NOMINAL INSTALLATION TIME
10 to 20 minutes

INSTALLATION PROCEDURE
Attach loops, tubes, or piezoelectric sensors and AC or solar power (if used).

SOME STATES CURRENILY USING THIS EQUIPMENT
Florida, Georgia, Hlinois, Maryland, New York

OTHER COMMENTS
Configuration varies with number and type of sensors connectors desired.

GTRI COMMENTS
Piezo-Loop-Piezo

-_——e on a a a oe oe ce a i a a a ee



2

Time interval

m1 6120~«93 «1% 1S

10

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‘#Comb {nat ions

Classification Matrix for IRD TC/C 530-4D/4P/4L

Figure 56.

(PR-L-PR) 2nd 48-Hour Test

136



5.2.10 Internationa] Road Dynamics, Inc. TC/C 530-4D/4P/4L_ (P-L-P)

The second sensor configuration used with the International Road Dynamics mode
TC/C 530-4D/4P/4L classifier was P-L-P using Philips vibracoax axle sensors. The results
of this classifier and sensor configuration are presented below.

5.2.10.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 58. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 70.8% of the vehicles (89.7% if class 2-3
errors not included). The number of vehicle axles was miscounted 7.25% (percent sensor
errors) of the time. There were less than 1.0% of the vehicles classified that were the result
of a suspected split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 59. The TC/C 530-4D/4P/4L classifier measures axles spacings, wheelbase length,
and overall vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XXVIII contains a summary of the results of the classification accuracy as a
function of percent vehicles with greater than two axles, air temperature and pavement

temperature.

140

~sS S22 eeee e  o



wa =

‘TECHNICAL REPORT STANDARD TITLE PAGE

Ty Repent Ne. 2. Government Accessien Ne. ‘3. Recipient's Corelog No.

por 9210

4.” Title end Subritie ‘5. Report Date

ACCURACY OF TRAFFIC MONITORING EQUIPMENT oer
[9. authar’ed F. Parlorming Orgenszenen Report No.

Bruce Harvey, G.H. Champion, S.M. Ritchie, C.D. Ruby

9, Perterming Orgenizetien Neme end Address 10, Werk Unit No.

Georgia Tech Research Institute

or Geant Ne.

Georgia Institute of Technology Ve Contra:
Atlanta, GA 30332-0821

33. Type of Repert end Penred Covers

12. Sponsoring Agency Nome ond Addre

Federal Highway Administration
Office of Highway Information Management

Final Report

400 Seventh Street, SW 44, Sponsoring Agency Code

Washington, D.C. 20590

13. Supplementary Notes .
Performed in cooperation with the U.S. Department of Transportation
Federal Highway Administration

16. Abstract

A total of 13 sensors and classifier configurations from 10 commercially available

equipment vendors were tested to determine their accuracy in classifying vehicles
into 13 FHWA vehicle classes, in measuring axle spacings, and in measuring
overall vehicle length. A majority of the participating vendors used a P-L-P
(piezo-loop-piezo) sensor configuration in the roadway, while the remaining
vendors used either a P~P or L-P-L sensor configuration.

Tests provided comparison of the vehicle-by-vehicle data from the classifers with i

ground truth data obtained from a video tape of the traffic stream in the test
lane. Vehicle classes and measurements were obtained from the video tape through
the use of a computer-aided data reduction system developed specifically for this

project.

Classification accuracies ranged from 78.8% to 96.2%, if class 2 (passenger
vehicles) and class 3 (small pickup trucks) are combined. The classification of
class 9 vehicles (a majority of the trucks) was very good on most classifers.
Classification accuracy, axle spacing measurement errors, and overall length
measurement errors appeared to be independent on the sensor configurations.

|

17, Key Words 18, Distribution Sterement

traffic monitoring equipment, No restrictions
vehicle classification, classifiers

mye

19, Security Clessif, (of this report) 20, Security Clessif. (ef this pege) 21. Ne, of Popes | 22, Price

Unclassified Unclassified

Form DOT F 1700.7 ta-63)



| THERMOCOAX NORCROSS NO: VB 901 D 002

* PHILIPS ELECTRONIC INSTRUMENTS COMPANY PAGE: 1/3
INDUSTRIAL AUTOMATION DIVISION
2975 COURTYARDS DRIVE
NORCROSS, GEORGIA 30071, USA DATE: 06/09/92
VIBRACOAX SENSORS DISTRIBUTION:

FIELD TEST PROCEDURE

APPENDIX:

THERMOCOAX REF:

CUSTOMER REF:

REV DATE AUTHOR DESIGN MANUFACTURING QUALITY
i) 06/09/92 . , Gi

4

This document Is the property of Philips/Thermocoax, Norcross, GA and cannot
be reproduced without written authorization.

Fx001



TRICKS OF THE TRADE: The reason
for allowing the epoxy, hardener and aggre-
gate mix to wait for some period of time is to
allow the exothermic heat of reaction to
develop to a temperature of 96°-100°F. The
colder the air temperature; the longer it takes
to do this. Keeping the full reaction mix in the
pail, allows the reaction to proceed as
indicated.

A glance at the graph will show that at air
temperatures above 90°F., there is no waiting
period. Ideally, READY-SET Pavement Grout
shouid be stored at 80°F at all times prior to
use. The 80°F. temperature (use the ther-
mometer) is high enough to safely mix, then
use the system without further waiting since

couid bring the temperature to 90°F. rapidiy.
Finally, heat applied to the cut groove from a
propane torch will both dry and heat the
groove. Carefully lay your hand upon the
pavement next to the groove. if the pavement
feels slightly hotter than your hand, the
temperature will be slightly above body tem-
perature. At this point, stop heating and begin
potting. Simply pour, spread and finish the
grout with appropriate tools (trowel, etc.) to a
smooth finish that is flush with the surface of
the highway.

NOTE: Always follow the sensor manufac-
turers recommendations for positioning the
sensor and any other techniques of impor-

tense which meayv he esunneacted in their
the actual mixing develops frictional heat and presentation. ee IIIS
PROPERTIES @ 77°F.
Typical Values ASTM Method |
Shelf Life 2 years NIA
Mix Ratio 4.6:2:20(A:B: Aggregate) N/A |
Viscosity Pourable NIA
Pot Life (Full Mix) 28 minutes . NIA
Hardness (Shore) 87-D to 90-D D-2240
| Tack-Free (10 min. wait) 77°F. 1/2 hour NIA |
Tack-Free (30 min. wait) 55°F 1/2 hour N/A |
Compressive Strength 8,000-10,000 psi D-695
Bond Strength 500 psi C-321
Water Absorption 0.30% D-570
re ee ee a ror aranion of tis Eystem. Your evaluation, of course. wit be neneesary in eer i determine ine
CAUTION: can cause skin iriation, Wear protective clothing. Wash conteminted skin with soap end water - NEVER SOLVENT. In case of
‘eye contact, fush with water for 15 minutes; Contact a physicien immediately.
FOR PROFESSIONAL USE ONLY

— — — —_



5.2.8.3 Seven-Day Test .

The results of the 7-day test to determine long-term statistics on classification

accuracy, vehicle count and axle count are summarized in Table XXIV. The totals for the

entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the
first and last full days recorded of the seven days.

Table XXIV. Long-Term Count/Classification Accuracy

TimeMark Delta 0

—
Total
Grnd Truth
Andes 40170 75831 64339 184.85 172.32 - 208.87
Class 1 88 292 -204 30.14 30.00 11.49 |
Class 2 26840 12876 13964 208.45 213.69 298.58 |
Class 3 + 16803 3754 13049 447.60 444.17 567.24
Class 4 119 358 -239 33.24 35.19 24.24
Class 5 1555 977 578 159.16 86.02 202.25
Class 6 + 597 659 ~62 90.59 96.55 88.89
Class 7 6 4 300.00 _ 100.00
Class 8 689 609 80 113.14 118.32 147.62
Class 9 8119 6591 1528 123.18 118.72 137.25
Class 10 91 42 49 216.67 200.00 300.00
Class i 209 167 42 125.15 117.56 134.38
Class 12 57 50 7 114.00 130.00 130.77
Class 13 0 2 -2 0.00 0.00 0.00
Class 15 L 0 0 0 ~ ~- - I
— Ce ae imme
130

Ree eee ee ee



5.23.2 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations for
lanes 1 and 2 are presented in Figures 38 and 40. The classification matrix is presented in
both absolute numbers, and percentages. The classifier designated lane 1 correctly classified
79.0% of the vehicles (96.2% if class 2-3 errors not included). The number of vehicle axles
was miscounted 1.19% (percent sensor errors) of the time. The classifier designated lane
2 correctly classified 79.1% of the vehicles (96.2% if class 2-3 errors not included). The
number of vehicle axles was miscounted 1.07% (percent sensor errors) of the time. Less
than 0.5% of the vehicles classified by either of the lanes were the result of a suspect split
or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figures 39 and 41 for lanes 1 and 2, respectively. The GK-6000 classifier measures axles
spacings and wheelbase length. The measurement error statistics (mean and deviation) for
all measurements are included in the figure as a function of measured vehicle speed (mph).
Note that all measurements are in feet.

Tables X and XI contain summaries of the results from lanes 1 and 2, respectively,
of the classification accuracy as a function of percent vehicles with greater than two axles,
air temperature and pavement temperature.

91



downloads took generally greater than 15 minutes. The data also inexplicably
ended in one file 6 hours before the end of one of the downloaded files.

e PAT_Equipment Corporation AVC-100 (P-L-P) - This classifier appeared to
operate correctiy most of the time during the test, but the reporting software
required to convert the binary data files into readable text files could not
convert the data files. The problem is still under discussion with the vendor.
The classifier also appeared to be having classification problems a couple of
times. These were checked out using the other AVC-100.

e PAT Equipment Corporation AVC-100 (L-P-L) - Two small gaps (less than
15 minutes) occurred when the equipment was intentionally disconnected to
check out an apparent problem with the other AVC-100.

e Diamond Traffic Products TT-2001 - The last 16 hours of data were lost when

the internal battery in the classifier malfunctioned. The unit would not
operate even when the charger was connected to the unit. An external

battery was used during the remaining 5 days of the 7-day test.
3.2.3 Seven-Day Test
3.2.3.1 Test Date and Conditions

The 7-day test was conducted September 9 - 16, 1993 in conjunction with the second
48-hour test. The air temperature during the test ranged from 50 degrees F to 86 degrees
F. The pavement temperature ranged from 61 degrees F to 117 degrees F. The weather
was partly cloudy and there was no precipitation during the test. Like the second 48-hour
test, this test was scheduled in the hopes of rainfall, but the only rain was a brief sprinkle
which did not register on the rain gauge or significantly moisten the pavement.

The traffic during the test was typical traffic for the site. There was no traffic
congestion during the test and the average speed of traffic was typically near 65 MPH. The

average daily traffic in the test lane (as determined from the video data reduction) was
approximately 10,100 vehicles.

3.2.3.2 Participating Vendors

The participating vendors for the 7-day test are the same as those for the second 48-
hour test. The road tubes used for the augmented tube test did not last the entire 7 days,
but did last through one full day of the detailed recording period (48-hour test).
3.2.3.3 Problems and Exceptions to Test Procedures

No notable problems with the test procedure occurred during the remaining 5 days

31



GOLDEN RIVER TRAFFIC LIMITED

y~-9.0"

EQUIPMENT
CABINET

Note: Both sensors
ore 7'-10.8" tong

Figure 17. GRI Installation Configuration Drawing

37



5.2.12.2 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 66. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 11.0% of the vehicles (11.8% if class 2-3
errors not included). The number of vehicle axles was miscounted 11.65% (percent sensor
errors) of the time. There were problems involving the recording software for the classifier
during this test. These problems occurred after an upgrade to the software was received
between the first and second 48-hour tests. The problems are associated with the data
recording and not the actual classifying of vehicles.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 67. The TT-2001 classifier measures axles spacings, wheelbase length, and overall
vehicle length. The measurement error statistics (mean and deviation) for all

measurements, and the overall Jength percentile Stat tics are included in the figure asa
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XXXIV contains a summary of the results of the classification accuracy as a
ith oreater than hug axles air temperatire and pavement

function of percent vehicles v “7
TunCuON Gr percent venicies With greater tinan two axes, air temperature ana pavement

temperature.

158

ee oe (ee |

ee ee a



Axles Spacing Statistics

Mean

0.178

0.218

Figure 35. Measurement Accuracy Versus Speed (MPH)

geesgians °

2PPerevuoDoe
=
a

NRE

Vbhd

Peek GK-6000 (Lane 1)

86

Veh axte_spacings

1 1

1 1

4 5

6 S

3 6

188 468

858 = 2016

2095 = 4913

2632 4985

1186 1625

203 27
32

7231 (14339

Vehicles

1
4
4
6
23
188
B58
2095
2632
1186
203
32
7231

- ist 48-Hour Test



Tiree ee wer ue Parranrnrmrrans wee

JAN 15 ’°S3 1z'48 LOCAL ASSOCIATES 223-387-4957

INSTALLATION NOTES

Max! Replaceable Axle Sensor: Piezo Electric
These sensors should only bs installed in Gates Max! Housings.

insort the sensor and tap Intoits seated position. If this is done fom the centre out, in each

Uhection, any possibilliy of kinking the sensor can be avokied. The sensor should be 2 tight
fit, but excessive forca should be unnecessary.

Check the height of the fitted sonsor above the housing surface. This is specified at 3mm.
Avernis: caliper gauge willbe found useful. Higher protrusion indicates Imperfect seating
and should bp rectified before procaading further: check for foreign matier between the
senior and housing. Ensure thal flexing at cable exit is zero as this will flex break the feader

Tighten down the retaining screws. A battery powered slecitic screwdriver makes Ahls
Quicker. Fill in the screw holes wilh plasticing.

Fittihe space al pach endo! the sensor, alter dam removal, with further plasticine. if particular
Care is taken at the cable exitend, and the pissticine pushed into the condull opening, further
sealing of the cable can be achieved to halp pravent ullimale moisiyie ingress,

Replacement is straight forward, Remembering to atlach a teader cord to the old signal cable

Can save p lot of frustration! Plasticine sealer should again be used to re-seal both screw

eee nd the ends of the channel. With experience. roplacement can be readily achieved
10 minutes,

‘The securing bolts in the base of the housing shouts bs checked for protrusion and security
whanever sensors are replaced. These bolts mus! be installed flush or slightly below the
bass, lalture to do this will result in reduced sensor life.

Kwillbe necessary to allow the Installed sensor to “bed-in”. Thisis achieved by allowing traffic
to flow treely over the installation for a period of time depending on fiow rates.

This will achieve a much cleaner signal for tuning purposes.

Pas



the pavement and through the slot cut in the paved shoulder. Place the
wire into the loop cuts pressing the wire to the bottom of the cut. The
GaDOT installation crew used a pavement saw blade mounted to a handle
that allowed it to roll freely to roll the wire into the cut. Install the
required number of turns then route the wire back to the equipment
cabinet. Leave an extra few feet of wire at the cabinet to allow for twisting

and routing.

5. Twist the leads by stretching the wire out straight and placing the ends into
the chuck of a drili. Operate the drill until the wire has approximately
three turns per foot. Route the wires through the conduit (if used) to the
box. Whether conduit is used in the trench or not, conduit is always run
from the trench up to the equipment box.

6. Fill the cuts with 3M Loop Seal. The sealer can be applied under wet
condition without any apparent problems. Cover the top of the cuts with
sand or glass beads. Clean up any excess loop sealer or debris.

7. Test each loop using the digital test instrument supplied by the GaDot.
The tester measures the inductance of the loop and indicates the loop
frequency stability.

2.2.3 System Testing

After the sensors are installed, the equipment is installed in the cabinet and
connected to the sensors. When the lane has been opened and the traffic is travelling
over the sensors, the classifier is adjusted if necessary and is checked for normal
operation. The vendor makes the determination as to whether the classifier is ready for

the evaluation.

it



— {

214



en I a ee a ee)



m@ mM eePEeen ae SS Pee See wee ih a ee

POLE CAMERA

MOBILE TRAILER

Figure 1.

VENDOR EQUIPMENT
(VEHICLE CLASSIFIERS)

Test Instrumentation

Conceptual Drawing



Table EX. Accuracy Summary for Peek GK-6000 (Lane 2)

1st 48-Hour Test

0-20 2.43 61 93.5 0.083 | 0.486
20-40 412 765 92.2 0.075 | 1.426 * .
40-60 5.17 92.8 93.1 0.019 }' 0.579
60-80 16.30 84.4 84.4 1.119 } 15.00
Air Temp
50-59 7.72 86.2 86.6 0.044 | 0.703
60-69 338 89.6 92.9 0.029 | 0.556 * .
70-79 3.29 786 92.7 0.065 | 1547
80-89 488 742 S24 0.113 | 1364
Pav Temp
60- 69 11.30 8531 85.6 0.414 | 9.463
70-79 3.08 88.9 93.1 0.020 | 0.537
R0- 89 3.285 80.1 93.1 0.043 | 1.622 * °
3.28 T12 925 0.113 | 2.123
3.24 739 93.4 0.133 | 1.244
441 74.0 92.0 0.094 | 0,821
— es
$0

me eo

m= @& i mm om

is =~ mm

i—-_ om

— = Gn



Table XXIX. Accuracy Summary for IRD TC/C 530-4D/4P/4L
(P-L-P) 2nd 48-Hour Test

Air Temp
60-69 5.45 714 92.5 0.024 | .744 | -2306 9.634 93.06 | 44.24
70-79 437 T4a2 94.0 0.030 | 534 | -2.143 | 11.026 | 94.68 | 49.76
80-89 2.80 768 95.7 0.040 | .603 | -2.030 9.847 93.95 | 46.41
Pav Temp
60- 69 423 ng 93.6 -0.016 | .793 | -1955 | 10.302 | 9530 | 48.96
70-79 719 TI 911 0.046 | 620 | -2.260 | 10.393 | 94.21 | 47.72
80- 89 553 741 93.0 0.025 | 528 | -2.116 | 11.871 95.67 { 52.17
90- 99 2.66 748 955 0.018 | .739 | -1948 | 10.259 | 94.43 | 49.19
100-109 2.18 75.7 95.9 0.024 480 | -2.404 9.670 92.26 | 42.46
110-119 1,786 8.847 92.97 } 45.20

147



2 13 4 15

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2nd 48-Hour Test
150

20116
20654
6583
11666.
104

144
4“

2156

1681

Classification Matrix for Golden River Marksman 660

#mi styped:
#eensor err:

Missing Vend:

#orrect:

Wendor:

#extra Vend:
#Splits:
#Combinations:

Weal:

Figure 62.



5.2.12 Diamond Traffic Products TT-2001 (Autologger Maxi)

The Diamond Traffic Products model TT-2001 classifier was tested using two
different sets of sensors. Each set of the sensors was used in a P-L-P configuration. The
first set of sensors used Autologger Maxi piezoelectric axle sensors. The results of this
classifier using the Autologger Maxi axle sensors are presented below.

5.2.12.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 64. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 73.1% of the vehicles (92.0% if class 2-3
errors not included). The number of vehicle axles was miscounted 3.17% (percent sensor
errors) of the time. There were less than 0.5% of the vehicles classified by the TT-2001 that
were the result of a suspected split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 65. The TT-2001 classifier measures axles spacings, wheelbase length, and overall
vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XXXIII contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

154



ee ee ee ee oe

om:

2.3.3. PAT Equipment Corporation

PAT installed two AVC-100 classifiers each with one set of sensors. The sensor
layout is shown in Figure 7. The first unit uses one Philips piezoelectric axle sensor and two
four-turn loops. The second unit uses two Atochem piezoelectric axle sensors and one four-
turn loop. The rutting at the location of axle sensors 1 through 3 was 11/32, 12/32, 11/32,
Tespectively. The installation was performed on 12/9/92. The sky was overcast, and the air

temperature was 38° F.

The general axle sensor and loop installation procedures were followed. The slots
were dried and preheated using kerosine "torpedo" heaters. No duct tape was used along
the top of the slot or on the sensor. Care was taken to scrape off any epoxy on the
pavement surface, and epoxy on top of the sensors was smoothed off flush with the road
surface. The epoxy used was E-Bond G-100. The Atochem axle sensors were pre-bent
slightly to conform to the local rutting, and were installed using only two leveling plates.
The philips sensor was not pre-bent; it was installed to be flush in the rut, and the low spots
were covered with epoxy. Since the ambient temperature (38° F) was too low for efficient
curing of the epoxy, all three sensors were cured using torpedo heaters.

The sensor profile in Figure 8 shows that the number one sensor is flush with the
pavement in the wheelpath as intended, and is below the pavement everywhere else. The
number two sensor is very low (-0.3 inches) near the solid line, but is near or only slightly

below the pavement in the wheelpath and beyond. The number three sensor is at -0.05 to -
G.13 inches from the solid line out to well beyond the wheelpath.

.15 inches rom the sold line out eli beyond the wheeipat.

Axle sensors were tested with an oscilloscope and were all working properly. Loops
1 through three measured 143, 146, and 145 microhenries, respectively, and demonstrated

good frequency stability.

The classifiers were installed in the cabinets and were tested. The vendor indicated
that one classifier.was not working and that the other classifier was functional but missed
too many axles. The vendor returned on 5/5/93, repaired the classifier, and added an
enhanced printed circuit card. The axle sensor signals were too low and variable. In order
to get acceptable signals, strips of bituthane tape approximately one inch wide were placed
over the low ares of each sensor to build them up to pavement level. Both classifiers were
then approved by the vendor for testing.

19



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3 AIPRRISER 2
2} gecicncesces |
Bigudagsen” 8

Length Percentile Statistics

Speeds

Wheelbese Statistics

Speeds

Vehicles.

sTD

Mean

Vehicles

ean = STD

AMSSARSSER

1

2

°

1
16
54
157
3S
32
2

1

0.000
1.015

g

0.000
8.033
0.000
0.916

9.000
200
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70.535 0.946.

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ae
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26.100

cy

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30.0-34.9 32.245
35.0-39.9 0.000
45.0-49.9
50.0-54.9
55.0-59.9

60.0-64.9

14.75

94.06

‘Overalt

70.552 2.789 404

Overal\

2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH)

Diamond TT-2001 (Autologger)

Figure 67.

| a ee

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5.2.4 PAT Equipment Corporation, Inc. AVC-100 (P-L-P)

PAT Equipment Corporation, Inc. loaned two model AVC-100 classifier for use in
the project. The first was setup in a P-L-P sensor configuration using Atochem Roadtrax
Series P’ axle sensors. The equipment appeared to operate normally during all of the
testing sessions. However, the reporting software provided by PAT Equipment Corporation
failed to convert the binary data files into ASCII (text) data files which could be used to
perform data reduction. After this problem was discussed with the technical representative
from PAT Equipment Corporation the binned data for part of the seven day test was
recovered. No data from either 48 hour test was recovered.

100

lead a nn a a ee



Plezo-Electric
Data Sheet No. 1

8. Scrape excess adhesive off the road surface, using it to cover the ends of the sensor and
the cable. Leave sufficient adhesive to just cover the feathered edges of the sensor. This is
to avoid any edges being visible, and to prevent damage from vehicles braking over the
sensor, and from snow ploughs.

Note: In warm weather the adhesive goes off very rapidly.

9, Whilst steps 6 - 8 are being carried out, the whole length of the sensor should be covered
with a piece of timber 50mm wide, this being weighted down sufficiently to hold the sensor
in position in the road surface. (Small oil drums filled with water and placed 500mm apart
would be suitable). The sensor is correctly positioned when the extremities of the domed
section are almost in contact with the road surface, apart from a thin layer of adhesive.

10. When the adhesive has gone off sufficiently to bold the sensor in position, wipe along its
length with solvent and a cloth to remove adhesive from the domed surface.

‘The information in this Da et oe oe ee ee a oe inet oe oe
suitability for their application. TAAFAC 2000 UMITED will not be fiabic for consequential damage arising from the wee
of these products. In line with our policy of continuous product development TRAFFIC s060 LAATED reserves the right

so amend specifications and prices without prior notice.

Page 4 Mar3992



Table XLI. Overall Length Measurement Errors
(All measurements in feet)

Equipment Standard
Vendor Deviation
Mikros TEL-2CM L-P-L 1 2.093 2.549
Systems (Philips) 2 -2.167 4.031

Peek Traffic, | TrafiCOMP P-L-P 1 N/A N/A
Inc. mw (Philips) 2 N/A N/A

P-P 1 N/A N/A

GK-6000 (Philips) 2 N/A N/A

P-P 1 N/A N/A

(Philips) 2 N/A N/A

PAT AVC-100 P-L-P 1 N/A N/A
Equipment (Atochem) 2 N/A N/A
Corporation, AVC-100 L-P-L 1 N/A N/A
Inc. (Philips) 2 N/A N/A

MITRON MSC-3000 P-P 1 N/A N/A
Systems DCP (Autologger) 2 N/A N/A

Corporation

Electronic HESTIA P-L-P 1 0.598 2.157

‘Control (ECM) 2 2.232 3.073
Measure
TimeMark, Delta P-P 1 N/A N/A
Inc. (Philips) 2 N/A N/A
International TC/C 530- PR-L-PR 1 -1.321 11.302
Road 4D/4P/4L (Dynax) 2 -1.739 10.952
Dynamics, Inc. P-L-P 1 1.154 11.423
(Philips) 2 -2.152 10.493
Golden River Marksman P-L-P 1
Traffic Ltd. 660 (Traffic) 2
Diamond TT-2001 P-L-P 1
Traffic (Autologger) 2
Products P-L-P 1
2
le

179



Plezo-Electric
Data Sheet No. 2

Cable Data

Outer diameter: 27mm
Piezo-electric polymer: polyvinylidene fluoride (PVDF or PVF2)
Piezo-electric coefficient: 3pCiN at 23°C

Capacitance: 850pF/m
‘Temperature range: = 40°C to +60°C
Sensor output signals

These graphs show actual responses obtained from a TRAFFIC 2000 piezo-electric sensor bonded into a
road surface, during the passage of various vehicles. Note that the signal level is dependent upon the rubber
profile selected, and upon the signal conditioning equipment used.

‘

3

Output, volts “ouput, votts
L 2
1
r 1
2
L - Car, 15 mph
2
t “1 Capt, vor
ecb
L wl
Car, 50 mph eat
eat
8 a Car, 2 mph, 1 ade only;
j L Oumar,
volts an
ap . ‘Output, votts
ze bend
2b
ah ose
: HGV, 20 mph - Bicycle, 10 mph
‘6 ow

‘The information in this Data Sheet is believed to be correct. Intending users should carry out their own tests to establith
‘suitability for their application. TRAFFIC 2000 LAATED will not be liable for consequential damage arising from the wee
(Of these products. In line with our policy of continvous product development TRAFAC 3000 LMITED reserves the right

to amend specifications and prices without prior aotice.

Jan.1992



“eee Eee ane eee were SsHneny sanerenw Feuve

JAN 15 ’S3 12:46 DOCAL ASSOCIATES 203-307-a0S7 ‘mn
wrologgeR Fo : HEC pee a Rowe NG
Axle Sensors rors 203-367 -9
January 15, 1989
Mr, Jerry Schitf
. Diamond Traffic

FAX 618-843-0270

Dear Jerry:

Please find attached copies of the installation instructions from the product brochure
for the Autologger range of piezo axle sensors. Towards the back of the packet are
two sections titied “Max! Replaceable Sensor” and “Maxi Replaceable Housing" where
you would find these Installation Instructions for the housings and the sensors. These
installation instructions are written for someone who is generally familiar with the
installation procedures for diferent types of plezo axle sensors. It is Important that the
instructions be carefully read and understood prior to the actual Installation. Please be
sure that if there are any questions or concerns that we are contacied well in advance
of the installation dats.

. There are several points that you should keep In mind regarding the installation of the
specific sensors that we have shipped to Glenn Champion, at GA Tech for Installation
In the Accuracy of Traffic Monitoring Equipment Project.

1. We recommend the use of E-Bond G-100 Epoxy or of Traffic Coll Adhesives Epoxy.

2. The installation Instructions diecuss the need to drill through the floor of the housing

- and install raw! plugs into the road surface below. It has been found that the use of
rawi plugs Is not necessary and in fact that they can reduce sensor life as they loosen
up and begin to come up from the sensor floor. ”

8. it is Very important that the epoxy used to install the housing be allowed to set very
hard before installing the eensor element into the housing. This will prevent the
housing walls from spiaying outward resulting in a loose sensor fit. in this manner,
when the sensor Is Instalied Into the housing I! will be a tight fit and may require the

* use of a rubber hammer or mallet. , :

* 4. Please note that the installation instructions indicate that the height of the fitted
sensor above the housing surface should be 3 mm. This is not the case with the
sensors that were shipped for this project which are designed to be flush fitting, le
there is no protrusion of the sensor over the housing. This is a design improvement to
reduce the possibility of something {ike a snow plow or muffler dragging the sensor

. element out of the housing.



Appendix 1

Notes On Epoxy

Page 7

The following epoxies are recommend for installation of Roadtrax Series P piezoelectric traffic sensors:

Dural 331LV epoxy is manufactured by Tamms Industries, Route 72 West, Kirkland, IHlinois

E-Bond G-100 epoxy is manufactured by E-Bond Epoxies Inc, Post Office Box 23069, 501 N.E.

33rd Street, Fort Lauderdale, Florida 33307. Tel: 305 566 6555

1, DURAL S31LV:
60146. Tel: 800 582 6670
2. EBond G-J00:
3. CONCRESIVE PASTE (SPL):

Concresive Paste (SPL) is manufactured by Master Builders Inc, 23700 Chagrin Blvd, Cleveland,
Ohio 44122. Tel: 800 227 3350.

Epoxy Type
CURE TIMES @ TEMP DURAL 33] E-Bond G-110 CONCRESIVE
| __ Usable Temp. (°F) 2510 90 °F 50 to 100 °F 25 t0 70 °F
Cure Time @ 100 °F N/A 2 Hours N/A
Cure Time @ 80 °F 20 Minutes 2.5 hours NIA
Cure Time @ 70 °F 40 Minutes 3 Hours 1 Hour
Cure Time @ 60 °F 1.25 Hours 6 Hours 2 Hours

Cure Time @ 50 *F

1.75 hours

14 Hours

3.5 Hours

+ These times are intended to comparison purposes only, They are only approximate, and dependent on many other factors. They
represent an approximate time at which to check the epoxy prior to allowing traffic to pass over the sensor.

In colder temperatures, store and mix the epoxy in a warm area. At warmer temperatures (above 70°F),
the Dural and the Concresive should be stored in a cool area such as an ice chest. If these thicken too
much from the cold, allow them to sit out for a period of time to gently warm them prior to use. There
are many factors which can influence the curing time, especially the use of "torpedo" heater. Plan to have
the required equipment on hand to get the job done in the allotted time. If traffic is allowed to pass over
the sensor prior to the epoxy being fully cured, the sensor will be forced too deep into the road, and
unacceptably low signal levels could result. Typically, Traffic Management does not allow for extra time
for road closure than that authorized. Plan ahead to avoid problems.

Elf Atochem Sensors inc, PO Box 799, Valley Forge, PA 19482 # (215) 666-3500 Fax (215) 666-3509



ee ee ee er ee ee ee ee ee

TIMEMARK, INC.
P.O. Box 12947
Salem, OR 97309
SALES REPRESENTATIVE
Dan Gossack (503) 363-2012
FAX (503) 363-1716
MODEL NAME

Delta II Classifier (Lambda)

GENERAL DESCRIPTION OF EQUIPMENT
The Lambda is a multi-sensor vehicle classifier for portable or permanent
installation. It will operate up to twelve sensors simultaneously including road

tube, inductive ioop, and piezo. The unit will count, provide binned speeds,
axle or length classifications, gaps, or provide per vehicle or time-tagged event
data.

METHOD OF OPERATION
The Lambda can be set up in the field with a built-in display and keyboard
or via local or remote link with a computer.

METHOD OF DATA STORAGE
The Lambda has battery-backed static RAM or can use PCMCIA Series 1
Flash memory cards. .

DATA STORAGE CAPACITY

The Lambda comes standard with 256K of onboard memory. The memory
card allows expansion of the memory up to the size of card available,
currently 20M with a 64M maximum.

VEHICLE CLASSIFICATION SCHEME
The Lambda has a 34 bin axle classification scheme based on Scheme F which
can be combined to the thirteen bin standard. Also will allow user defined
schemes to be loaded or processed from time-tagged events.

POWER SOURCE
The Lambda comes with a 6V - 10 amp-hour rechargeable battery which can
be connected to solar or other charging unit. The unit will run for 10 days
from full charge with eight loop capability.

OPERATING TEMPERATURE RANGE
The electronics except for the display will operate down to -20°C and up to
70°C (-4°F to 158°F)

OPERATING VEHICLE SPEED RANGE

The sensors will activate down to 5 mph and up to 120 mph but speeds
greater than 80 mph are recorded only as such.

211



5.2.7.3

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XXI. The totals for the
entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the

Seven-Day Test

first and last of the seven days.

Table XXI. Long-Term Count/Classification Accuracy
Electronic Control Measure HESTIA

a —
Total Total Total
Grod Truth Difference Percent
Vehicles || 63474
Axles 162780 148081 14699 109.93 110.01 108.78
= 1 101 0 101 ~ - ~-

H Class 2 30500 47439 -16939 64.29 6447 64.01 i
Class 3 | 19015 2660 16355 T1485 622,16 655.24 |
Class 4 | 135 9986 -9851 135 0.90 0.87
Ciass 5 1897 55 1842 3449.09 3420.00 2875.00
Class 6 | B38 21 507 319.48 254.76 =n500 |

L Class 7 | 8 63 -55 12.70 18.18 7.69
| Class8 ff 848 0 848 - - -

L Class 9 q 9804 0 9804 - - |
Class 10 | 106 0 106 - ~ -

i 0
0
i 9

12

121



5.2.123 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XXXV. The totals for the
entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the
first and last of the seven days.

Table XXXV. Long-Term Count/Classification Accuracy
Diamond Traffic TT-2001 (Autologger)

Difference _ Percent Percent
11318 25932 329.12 354.63
99403 N/A N/A N/A 252.10
Class 1 50 261 “211 19.16 - 11.54
Class 2 16987 1989 14998 854.05 = 851.83
Class 3 10457 1158 9299 903.02 = 726.35
|| Class 4 | n 24 47 295.83 = 266.67
Class 5 | 1226 313 913 391.69 - 384.62
Class 6 533 338 195 157.69 - 122.77 _|
Class 7 | 7 7 ) 100.00 - =
Class 8 + 644 ng -15 89.57 - 66.80
Class 9 6956 3563 3393 195.23 = 153.83
Class10 ff 81 a) 1 115.71 - 7391
Class 11 183 190 7 9632 = 72.58

162

— = mm


2.4 INSTALLATIONSUMMARY AND CONCLUSIONS

Over the period of November 1992 to March 1993 eleven classifiers from nine
vendors were installed using fifteen test sensor configurations. Fifteen loops and twenty-eight
axle sensors were originally installed. Six axle sensors were replaced and two were
abandoned for a total of thirty-four installed and twenty-six functioning. Six different types
of axle sensors were installed using five different types of epoxy. The procedures used by
each vendor for sensor installations were the same except for a few minor details. The only
significant difference in installation procedures was for the Autologger replaceable type
which required some special procedures.

There were no problems encountered with any loop installations; however, there were
quite a few problems encountered with the axle sensors. The biggest problem was low
output levels and large differences in output levels across the length of the sensor. Some
of the variation could be caused by manufacturing variations, but most is caused by the
height profile of the installed sensor. Areas of the sensor below pavement leve] have a
lower output voltage causing classifier sensitivity problems; areas above pavement level
have a higher output level but subject the sensor to possible damage.

When larger signals are presented to the classifier, overshoot and undershoot of the
signal will cause extra axle counts if the detection threshold level is set too low. The
threshold level must be set low enough to detect small cars but high enough to avoid extra
axle counts. Variation of the output level along the length of the sensor, due to installation
or manufacturing, make this setting more difficult. The field repair for the sensor profile
problem, bituthane tape over the low spots, had to be employed for thirteen of the twenty-
six functioning sensors to achieve good classifier performance. Most of the difficulty with
sensor profile can be attributed to the rutting present at the site. Even though the rutting
was not too severe, the rigid sensors could not be made to conform well to it.

Other problems encountered with axle sensors included snow plow damage of the
Autologger mini-replaceable (which extended over the pavement level), cracking and
chipping of epoxy on one of the IRD Philips sensors requiring repair, and poor coax
connections to classifiers. The one epoxy failure was probably due to a premature epoxy
cure not allowing the sensor to be installed below the road surface as designed.

The axle sensor replacements included, two of MITRON’s Autologger Mini
replaceable sensors (for low output levels), three of GRI’s Traffic 2000 sensors (one to
relocate closer to the loop and two for low output), and one ECM sensor (for low and
erratic output). The abandoned sensors were two of TimeMark’s Philips sensors.

In addition to the axle sensor problems, several problems were encountered with

initial setup of the classifiers. Some problems were actually sensor related (such as difficulty
in compensating for low or variable axle sensor output) and some were faulty electronics or

43



| ee ee Oe on |

Table XI. Accuracy Summary for Peek GK-6000 (Lane 2)

2nd 48-Hour Test
96.2
0-20 0.83 713 96.6 0.014 { 0.316
20-40 127 80.5 95.7 0.003 | 0.360
40-60 3.41 89.8 95.1 0.038 | 0.286
Air Temp
60-69 1.73 82.0 955 0.036 | 0.307
1-79 1.07 786 96.2 -0.031 } 0.305
80-89 0.77 78.9 97.0 0.056 } 0.355
Pav Temp
60- 69 3.12 953 953 -0.043 | 0.334
70-79 1.15 84.9 96.8 -0.016 | 0.305
80- 89 1.62 80.6 96.5 -0.025 | 0.313
90- 99 0.87 714 963 0.003 | 0.318
100-109 0.72 719 96.0 0.043 | 0.328
110-119 0.80 75.0 98.0 0.027 | 0.299

joes Not Measure Overall Vehicle

agt

97



traffic caused the program to determine the splits or combinations occurred when, in fact,
there were none. These types of errors were few and far between, and did not significantly

impact the results.
46 TYPICALANALYSIS OUTPUTS
Figure 24 | is an 3 example of the Output 0 of the BINNED program. The first line is the

input file name (standard formatted file), Then ihe date is shown followed by the binned
data for that day. The first two columns are the start and stop time for the bin given as
HHMMSS, where HH is the hour (24 hour clock), MM is the minute and SS is the second.
The next two columns show the total axle and vehicle count for the bin. The next fifteen

columns show fe ahe 19 TENA wabtcle claccec clase te
columms show the vehicle count in the 13 FHWA vehicle classes, the class 14 (which is

unused by all the classifiers), and class 15 (usually used for unknown vehicle types). The
remaining three columns list average speed in MPH (if given by the classifier), the number
of vehicles with greater than two axles, and the percentage of vehicles with greater then two

totale are slat,

avlac Fin A TAn: ened
axles. Daily totals are provided, and 7-day totals are calculated for the long-term test.

Figure 25 shows and example of the ANALYZE programs output to the
TABLE. OUT file. This file contains a classification matrix, and statistical ‘summaries of the
axle spacing, wheelbase, and overall length measurements. The first line contains the
filename for the vendor classifier data, and the second line contains the time interval
(maximum delta time allowed) used for the ANALYZE matching algorithm. The first
matrix depicts the total vehicles as classified by the vendor classifier and the ground truth

date The wandae claccar are suehared at the tan nf the ecloeins on; eer ett?
data. The vendor classes are numbered at the top of the columms, and the ground truth

classification is numbered at the left of the rows. In other words, the number in the column
C and row R is the total number of class R vehicles (as determined from the CVCRS) that
were classified as class C by the vendor classifier.

The second matrix in the TABLE.OUT file is identical to the first, except the totals
are expressed as percentages of the total vehicles in the class (ground truth). Following the
matrices are the totals of the real (ground truth) vehicles, the vendor vehicles classified, the

evar af ws. ze weeeees] et aviac
number of mistyped vehicles, the number of sensor errors detected (mis d axles), the

number of extra vendor vehicle not in the ground truth data, the number of missing vehicles
not in the classifier’s data file, and the number of correctly classified vehicles. Also totalled
is the 1 number of split and combined vehicles s suspected by the ANALYZE program. The

de: he the ANAL Vv70o
file of split and combined vehicles detected by the ANALYZE program was manually

reviewed to determine the actual split and combination count for the classifier.

Following the totals are summaries of the length measurement statistics for the

classifier. The statistics on the accuracy of axle spacing, wheelbase and overall vehicle

length measurements are summarized as a function of speed. The speed bins are 5 MPH
wide from 30 to 80 MPH. The mean and standard deviation of the measurement, and the
total number of vehicles in the speed bin are listed. For the axle spacing measurements, the

4 axle spacings are on a S-axle track) for each sneed bin are alsa

total axle enacines (i
total aue spacings (i.c. 4 axe spacings are on a JS-aue trick) ior cach Speed vin are aiso

61



2.3.1 Mikros Systems

Mikros installed a model TEL-2CM classifier with two, three-turn Joops and one
Philips axle sensor. The sensor layout is shown in Figure 3. The rutting at the location of
the axle sensor was 5/32 inch. The installation was performed on 12/3/92. The weather
was clear, and the air temperature was 57° F.

The general axle sensor and loop installation procedures were followed. The slots
were dried with compressed air, and the epoxy was cured under ambient conditions (no
heaters were used). Two layers of duct tape were used along the top of the slot. A strip
of duct tape was also used on the top of sensor; it was peeled off after the epoxy cured
resulting in a clean sensor surface. The aluminum channg) of the sensor was cleaned with
solvent prior to installation to insure proper bonding with the epoxy. The epoxy used was
Traffic Coil (manufactured by Astor-STAG). The axle sensor was installed using 4 leveling
plates.

After the installation was complete, the sensor height profile relative to the pavement
surface was measured to determine how well the sensor conforms to the road surface. The
Measurements were performed by placing a special jig over the sensor with supports resting
on the pavement on either side and measuring the height of the sensor surface with a dial
caliper. The sensor profile is shown in Figure 4. A sensor height of zero indicates the
sensor is flush with the surrounding pavement; negative heights indicate sensor surfaces
below pavement level. The rutted area of the road extended from approximately 1.5 feet
to 2.5 feet. The plot shows that the sensor was as much as 0.1 inches above the road surface
level in the rutted wheel path and was as mouch as 0.18 inches below the surface at around

3.5 feet.

Initial tests of the axle sensor with oscilloscope verified that it was operational;
however, the output levels vary with the position of the vehicle’s wheel across the length of
the sensor. The sensor performance was determined to be adequate by the vendor. Testing
of the loops indicated 89.6 microhenries for loop 1 and 91.2 microhenries for loop 2 with

stable frequency readings.

Classifier installation, checkout and training were performed on 12/17/92. The
vendor indicated that the classifier was functioning properly and was ready for testing.

The coax and loop leads were broken on 1/28/93 by the power pole installation
vehicle. On 1/29/93, the leads were spliced (soldered) and encapsulated inside a six inch
section of PVC pipe filled with silicone caulk. The new leads were mun in a deeper trench
routed away from traffic in the mobile office area. System retests by the vendor indicated
that the sensors and classifier were functioning properly.

13



52.22 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 32. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 74.8% of the vehicles (93.2% if class 2-3
errors not included). The number of vehicle axles was miscounted 3.53% (percent sensor
errors) of the time. Note that the TrafiCOMP III output was not time stamped with seconds
and manual aligning of the data was required. Therefore, identification of splits and
combinations could not be accomplished.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 33. The TrafiCOMP Ii classifier measures axles spacings and wheelbase length.
The measurement error statistics (mean and deviation) for all measurements are included
in the figure as a function of measured vehicle speed (mph). Note that all measurements

are in feet.

Table VI contains a summary of the results of the classification accuracy as a function
of percent vehicles with greater than two axles, air temperature and pavement temperature.

719



— > a we oO ae oe eee eo ee ee oy

a

vee 213

TABLE OF CONTENTS (cont.)



9-12-93

184500
ieooce

191500
193000
1294500
200000
201500

1500

3000

4500
10000
11500
13000
14500
20000
22500
23000
24500
30000
31500
33000

34500

40000
41500
43000
44500
50000
5:

190000
191500
193000
194500
200000
201500
203000

381

327

179

148

210000
211500
213000
214500
220000
221500
223000
224500
230000
231500
233000
234500

211500
213000
214500
220000
221500
223000
224500
230000
231500
233000
234500

POCOKODODOHOOODODDOOOCOOOHOOOKO

VoroorecaccocOHaDDOOMo

Figure 24.

2 3 4 5 6 7 8 9 10 Il 12
29013 0 ° 1 o 0 3 ° o o
iv i6é i 0 i} o o i 0 io °
21 «#10 o 2 1 ° O 2 ° O °
200«ol J oO ° o 1 4 o oO oe
22°77 o 2 o 0 1 ‘ ) a 9
Ie ii ° o 0 0 O0 2 ° o °
12 4 1 1 ° ° ° 3 0 ° a
1s oT 0 9 ° ° oO 3 ° ° o
19 9 ° a ° ° o 3 0 ° °
12 6 i ° o o o 6 ° o o

6 6 1 0. 1 o ° 2 oO i) 9

7 6 9 1 ° o ° 5 0 0 o

? 3 °o 1 o Oo oO ° ° a o

‘ 5 6 09 @© @ 0 5 o o 0

8 4 oO 2 1 o 9 o o co) °

6 3 1 0 1 o a 2 0 J °
17 7 1 1 ° o ° 3 o o Oo

5 7 4 ° o o 0 3 ° ° o
1200°«7 ° ° 1 ° ° 4 0 o 0

6 3 3 ° ° 9 ° 2 9 ° o

3 5 3 °o ° ° 0 1 ° Qo )
i3 8 oa 8 i a oo 4 6.6 s
17 4 ° o ° ° o 2 o o o
1s 5 o i ° ° ° 3 o ° o

9 9 ° ° ° o o 2 °o o .
10° o 4 ° ° ° ‘4 o 90 °
10 «10 o 4 o 0 o 64 0 o @
10011 0 ° ° 0 ° 3 0 0 6

° 3 a oO 9 4 ° ° °
9 4 o Q Q 8 o Qo o
o 2 0 0 0 7 @© 4 0
o o0 0 © 1 8 0 09 90
© 3 2 0 0 9 0 oO »B
o 2 12 0 0 7 oOo 2 »D
1 0 0 0 0 9 69 Oo ©
0 4 0 © O08 7 © 98 ©
@ i 0 0 8 $ G© 12 2
o 2 0 0 868 5 G0 2 6
o o 2 0 1 5 0 3 9
o 2 0 © 0 15 0 0 8
© 3 o© © © 30 09 0 8
© 1 1 0 0 6 O09 2 0
© o oo &© 3 10 0 89 8
®o o 1 0 ©O 33 0 0 9
o 0 60 0 8 4% 0 9 9
o 2 0 0 9 9 0 06 98
®o 1 0 © © 9 0 0 90
0 1 09 © @ 7 09 08 ©
o 4 0 © 9 7 0 0 0
34 «(169 36 1 21 S16 2 12 2

Example Output of the BINNED Program

62

»

POGDDDGB005D00000000000000000 &

eoeDo00 CONC COB00S000b0

os

SPEEDED CODDODODGODD00000900000 &

eoveKc eK e AO DOOD 00RD000D0



axles Spacing Statistics

Speeds = «Mean = STD

<0 10.818 11.181
30.0-34.9 0,000 108
35.0-39.9 0.513 496
40.0-44.9 0.441 0.799
45.0°49.9 0.180 G.447
50.0-54.9 0.159 0.368
55.0-S9.9 0.163 1.162
60.0-66.9 0.085 0.988
65.0-69.9 0.0465 0.706
70.0-74.9 0.009 0.526
75.0-79.9 0.030 0.299

80 -0.130 0.578

Overall 0.099 «1.113

Wheelbase Statistics
Speeds ean 87D

32.455 23.527
0.000 0.000
0.683 0.489
0.921 1.323
0.376 «60.371
0.372 0.874
0.316 0.921
0,180 1.025

79 (0.787

0.
0.137 0.716
Overall 0.191 1.637

Figure 27.

Length Statistics

Veh = axie_Spacings ‘Speeds Mean s1D Vehicles
6 8 0 39.353 27.719 6°
o o 30.0-34.9 0.000 0.000 0
3 4 35.0-39.9 3.787 2.020 3
" 3B 40.0-44.9 3.346 2.570 Ww
12 a 45.0-49.9 3.053 1.725 12
206 482 $0.0-54.9 3.253 1.989 206
TI0 1577 35.0-59.9 2.764 2.225 T10
4735 37 60.0-64.9 2.329 1.979 1735
1530 2661 635.0-69.9 1.701 1.669 1530
631 872 70.0-74.9 1.186 1.868 ei
152 168 75.0-79.9 0.925 1.076 152
8 9 >80 0.477 0.673 8
5014 9626 Overail 2.093 2.349 5036
‘ Length Percentile Statistics
Vehicles Speeds Mean STD Vehicles
6 <0 707.43 432.02 6
o 30.0-34.9 0.000 9.000 o
3 35.0-39.9 118.602 723 3
uv 40.0-44.9 113.616 14.954 u
2 45.0°69.9 111.109 = 7.331 12
206 30.0-54.9 111.339 7.713 206
710 55.0°59.9 109.764 11,165 710
4735 60.0-64.9 107.675 5.616 1735
1530 85.0-69.9 107.137 6.382 1530
631 70.0-74.9 106.106 7.773 61
152 75.0-79.9 105.907 7.457 152
18 >60 103.09 4.32 %
5014 ‘Overall 108.43 26.62 5014

Mikros TEL-2CM - 1st 48-Hour Test

+ 68

Measurement Accuracy Veraus Speed (MPH)



APPENDIX C

FLOW CHART FOR THE VEHICLE MATCHING ALGORITHM
OF THE ANALYZEPROGRAM

213



—-— es wwe eee ee ee et ee ee



Table X. Accuracy Summary for Peek GK-6000 (Laue 1)

2nd 48-Hour Test

Aatle
Total 79.0 0.004
% Trucks
0-20 0.94 TIA 96.7 0.023 | 0.329
20-40 150 80.4 95.5 0.001 | 0.401
40-60 154 923 96.9 0.084 | 0.305
Air Temp j
60-69 1.46 82.5 95.5 0.047 | 0322
70-79 16 B5 96.5 0.012 | 0.338
80-89 1.18 78.7 96.5 0.070 | 0.379
Pav Temp
60- 69 2.13 89.4 89.4 0.075 | 0.364
70- 79 137 86.0 96.0 -0.063 | 0318
80- 89 158 80.8 96.5 0.014 | 0.334
1.10 TA 96.0 0.008 | 0.332
0.97 716 96.1 0.048 | 0.397
1.08 752 98.0 0.035 | 0.286
le eet toms foe] ft
oes Not Measure Overall Vehicle

TM

96

mm © w= oe eo ae ol i tl

ee ee



5.2.1 Mikros Systems TEL-2CM

The Mikros Systems model TEL-2CM classifier used an L-P-L sensor configuration
and Philips Vibracoax piezoelectric axle sensors. The results for the individual tests are
presented below.

52.11 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 26. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 70.3% of the vehicles (82.5% if class 2-3
errors not included). The number of vehicle axles was miscounted 13.91% (percent sensor
errors) of the time. Less than 1.0% of the vehicles classified by the Mikros equipment were
suspected to be the result of a split or combination of an actual vehicle. .

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 27, The Mikros classifier measures axles spacings, wheelbase and overall vehicle
length. The measurement error statistics (mean and deviation) for all measurements, and
the overall length percentile statistics are included in the figure as a function of measured
vehicle speed (mph). Note that all measurements are in feet.

Table Hi contains a summary of the results of the classification accuracy as a function
of percent vehicles with greater than two axles, air temperature and pavement temperature.

66



nmeew ee meee eee eee ee

6& ANSWERS TO SPECIFIC QUESTIONS

The data analysis portion of this project was intended, in part, to answer eleven
specific questions. These questions will be addressed specifically in this section of the report
with references to related section of the Teport for additional information.

. . vehi .
Question 1. How Accurately do the various wpes_of vehicle classifiers sort the tratfic of the 13 FHWA vehicl >

Table XXXIX depicts the accuracy of each of the classifiers to sort the vehicle
stream into the 13 FHWA vehicle types. This table lists the percent of the vehicle stream
correctly classified and the percent sensor errors (axle miscounts) for each vendor and each
48-hour test. Note that the number in parenthesis in the "% Correctly Classified" column
is the percentage of correctly classified vehicles with classes 2 and 3 combined. Errors
between classes 2 and 3 are by far the most common errors since often time small pickup
trucks have shorter lengths and wheelbases than large cars. Therefore, it is often impossible
to correctly sort vehicles between class 2 and 3 based on axle spacing and length.

The accuracy of the classification appears to be inversely proportional to the ability
of the classifiers to count axles. Missed axles (referred to as sensor errors) seem to directly
relate to sensor errors and can be used as an indicator of overall classifier accuracy. Figure
72 in Section 5.3 plots the percentage of correctly classified vehicles as a function of the
percent sensor errors (miscounted axles). As the number of sensor errors increased the
accuracy of the classifiers declined almost linearly.

Question 2, For th hicles tt bei Jy classified by a device, i
class did the devices place the vehicle?

The classification matrices for each of the vendors are shown is Section 5.2. The
matrices show the count and percentage of vehicles that were correctly and incorrectly
classified into each of the categories. The classes into which an incorrectly classified vehicle
was placed varied somewhat between the individual classifiers devices. Some general trends

+ be noted.
can however be noted.

The primary misclassification noted in the test results was the classification of class
3 vehicles as class 2 vehicles. Since these two classes of vehicles often have similar overall
and Ibase lengths (the primary measures for sorting the vehicles), this error is easily
understood. Classifications of class 2 vehicles as class 3 occurred much less often than class
3 to class 2, but did occur in significant numbers.

Classification errors between all of the 2-axle classes (classes 2, 3, 4, and 5) were also
common. Again, there are a number of small buses and 5-tire trucks, and large cars and
pickup trucks with very near the same lengths and wheelbases. Therefore, differentiation

of the classes based entirely on axle spacing and length is nearly impossible.

173



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2nd 48-Hour Test
92

20116
13671
2750
155
539
6978
10325
Ww

B

Classification Matrix for Peek GK-6000 (Lane 1)

Missing Vend:
wcorrect

#istyped:
wsplits

‘#verdor
Wsensor err:
Wextra Vend:
Combinations:

#Real

Figure 38.



ee | |

-

Axles Spacing Statistics

Mean

7.506
0.140
0.203
0.260
0.175
0.166
0.193
0.164
0.162
8.186
D.191
9.170

0.172

STD

7.256
0.100
0.160

Ubeelbase Statistics

Speeds Mean,

<0 9.382
30.0-34.9 0.740
0.372
0.519
0.340
0.349
0.409
O.367
0.238
0.189
0.197
0.970

0.307

Figure 31. Measurement Accuracy Versus Speed (MPH)

Peek TraficomP

sto

Tir

Veh axle_Spacings

4 5

2 2

6 "1
a 3%
68 132
427 897
1666-3494
4367 «10307
3366 4965
1295 1316
324 321
Ey BM
12054 21520
Vehicles

4

2

6

18

6s

427

1666

4867

3366

1295

323

Mu
12054

ist 48-Hour Test



Axles Spacing Statistics Length statistics
Wean = STD Veh  Axle_Spacings Speeds Hean STD —- Vehicles.
7.023 2.404 1 4 <0 39.010 0.000 1
7.057 2.498 6 24 30,0-34.9 38.602 0.499 6
0.000 0.000 0 oO 35.0-39.9 0.000 0.000 o
-0.072 2.786 3 9 40.0-44.9 -0.337 0.537 3
0.113 0.230 38 89 45.0-49.9 -1.290 1.502 38
0.09% 0.332 397 836 §0.0-54.9 -1.223 2.732 397
0.257 5.287 1790 3578 55.0-59.9 -0.876 13.647 1790
0.091 0.454 4387 8934 60.0-64.9 -1-385 4.181 4387
0.103 0.470 heh T7209 65.0-69.9 °1-260 2.268 4424
0.138 263 1755 2173 70.0-76.9 -1.069 1.379 1755
0.121 265 330 366 75.0-79.9 -1.052 1.156 330
0.080 0.326 67 67 >80 -1.101 1.300 67
0.133 2.124 13998 = 23289 ‘Overall “1.196 5.845 13198
Wheelbase Statistics Length Percentile Statistics
Speeds ean stD Vehictes Speeds Mean = STD Vehicles
<0 28.090 0.000 1 <0 215.07 9.00 1
30.0-34.9 28.227 0.356 6 30.0-34.9 213.950 2.313 6
35.0-39.9 0.000 0.000 0 35.9-39.9 0.000 0.000 oO
40.0-44.9 0.217 1.560 3 40.0-44.9 100.109 1.880 3
45.0-49.9 0.265 0.241 38 45.0-69.9 95.707 5.170 38
§0.0-54.9 0.198 0.447 397 50.0-54.9 95.927 14.330 397
55.0-59.9 0.513 11.847 1790 55.0-59.9 96.801 28.774 1790
60,.0-64.9 0.185 0.609 4387 60.0-64.9 95.033 11.194 4387
65.0-69.9 0.167 0.470 4426 65.0-69.9 94.440 9.202 4424
70.0-74.9 0.161 0.285 1755 70.0-74.9 94.324 8.587 4755
75.0-79.9 0.134 0,266 330 75.0-79.9 94.476 8.355 330
>80 0.080 0.326 67 >80 4.52 11.25 67
Overall 0.234 4.436 13198 Overall 95.06 14.46 13198

Pigure 69. Measurement Accuracy Versus Speed (MPH)
Diamond TT-2001 (Philips) - ist 48-Hour Test

165



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(Philips) 2nd 48-Hour Test
168

14539
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Classification Matrix for Diamond TT-2001

dni styped:
#eensor err
Missing Verd:

wcorrec'
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Meals

Figure 70.



nee a

3. TEST SESSIONS
3.1. OVERVIEWOF TEST PROCEDURES

Each test was conducted using the following basic steps:
1L Camera/video installation,

2. AVC equipment installation,
3. AVC equipment start-up,
4. Video start-up,
5. Monitor video and AVC equipment, and record weather conditions,
6. Test shut-down,
and 7. Remove and store AVC equipment.

Camera and video installation involved placement of the video cameras and recorders

for traffic stream videc and lane-~change monitoring. The traffic stream camera (pole

camera) was mounted in a metal box at the top of a utility pole near the mobile office. It
was angled to monitor the traffic stream in a test area marked with a 40 foot long test area.
The video output was connected to a VCR in the mobile office for recording the video. The
camera was set to display time and date on the video output. Standard speed recording was
used for the detailed (48-hour) test periods and extended play recording speed was used for
the long term (7-day) test.

The lane-change monitoring camera was mounted in a modified traffic control box

located on the overpass at the end of the test area. It was angled to look directly between
the two westbound lanes and covering the entire test area. The video output was connected
to a VCR in a traffic contro! cabinet at the end of the overpass. This camera did not have
the capability to display time and date, so a time/date generator was installed between the
camera and the VCR. In this manner, the video was time stamped for use in the data
reduction. Extended play recording speed was used for all tests.

t installation involved the placement of each of the

iP
the appropriate traffic control box, connection of sensor leads, and check-out of yperation.
Some of the classifiers required the use of a personal computer (PC) in order to record
detailed vehicle-by-vehicle information. Others required occasional downloads of
information to a PC during the tests to avoid overflowing the internal memory of the
classifiers. The PCs needed by vendors were connected to the classifiers during the
equipment installation. The following is a list of the classifiers which required connection
to a PC during the detailed testing sessions:

Mikros Systems TEL-2CM - Connected to a PC running a monitoring program
provided with the classifier. The monitoring
program logged the  vehicle-by-vehicle
information and stored it on the, PC’s hard disk.

45



DIAMOND TRAFFIC PRODUCTS

ee | ,
rm 850

96"

EQUIPMENT
CABINET

Note: Both loops
ore 5X7

Figure 19.

41

Diamond Installation Configuration Drawing



nen Rem wee eee eee ee eo

Table I. Vendor Classifiers and Configurations Installed

LP-L, Philips Vibracoax

GK-6000

P-P, Philips Vibracoax
P-P, Philips Vibracoax

AVC-100
AVC-100

P-L-P, Atochem Roadtrax Series ”
L-P-L, Philips Vibracoax

MSC-3000
DCP

P-P, Autologger MINI

Electronic Control

HESTIA

P-L-P, ECM PB2N33/25

=|
P-L-P, Philips Vibracoax |
P’ |

|

TimeMark, Inc. Delta IT P-P, Philips Vibracoax
International Road TC/C 530- PR-L-PR, Dynax AS-400 (Resistive)
Dynamics, Inc. 4D/4P/4L P-L-P, Philips Vibracoax
! Golden River Traffic Marksman 660 | P-L-P, Traffic 2000
| Diamond Traffic TT-2001 P-L-P, Autologger Maxi
| Products P-L-P, Philips Vibracoax



{[Velene[2} - Rettme[2]]
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2.3.7 International Road Dynamics

IRD installed a model TC/C 530 classifier with two sets of sensors configured as two
lanes. The sensor layout is shown in Figure 15. The first sensor configuration uses two IRD
DYNAX AS400 resistive axle sensors and one four-turn loop. The second sensor
configuration uses two Philips piezoelectric axle sensors one four-turn loop. The rutting at
the location of axle sensors 1 through 4 was 6/32, 5/32, 5/32, and 4/32, respectively. The
installation was performed on 12/17-18/92. The weather conditions were: cloudy, rain
(in the morning), and 59° F on the 17th; clear and 58° F on the 18th.

The general axle sensor and loop installation procedures were followed. The slots
were cut on the afternoon of the 12/17/93, but because of the rain delay in the morning,
there was not sufficient time to completed the installation. Before opening the lane, the
slots were filled with sand to protect them from damage by vehicles. The next day the sand
was cleaned out of the sensor slots using compressed air and the slots were dried with hand
held propane torch being careful not to overheat the asphalt. Two layers of duct tape were
used along the top of the slot. The epoxy used was IRD System 400 for the Philips sensor
and Dural International Corporation 331 LV epoxy for the DYNAX sensors. The DYNAX
sensors were flexible and conformed well to the local rutting, and were installed using 5
special leveling plates. The plates have a slight hump in the center to allow the raised
surface of the DYNAX sensor to come up over the road surface slightly (approx 1/32). The
Philips sensors were installed using 7 special leveling plates that were drilled and tapped in
the center for a 1/4 inch bolt. The bolt is adjusted and the plate is tie wrapped to the
sensor such that the sensor is held down 3/16 inch below the road surface.

The DYNAX sensor procedure is to pour enough epoxy such that excess material
extrudes around the sensor. The excess is troweled off and smoothed using a putty knife.
Weights are placed on the leveling plates and the epoxy is allowed to cure under ambient
conditions.

The Philips sensor procedure is to pour 1/2 the required epoxy, place the sensor in
the slot and apply weights to hold it in place, let the epoxy partially set up then remove the
weights. After both sensors were installed, another batch of epoxy was mixed to top off the
slots flush with road surface. The epoxy is smoothed with a putty knife and allowed to cure
under ambient conditions. Sensor 3 had voids underneath due to insufficient epoxy on the
first pour and had to be pulled up so more epoxy could be poured in the slot. The epoxy
had started to harden and the sensor could not be pressed down fully below the road
surface.

The DYNAX resistive sensor operation was verified using an ohmmeter. The Philips
sensors were tested with an oscilloscope and were both working properly. The loops
measured 152 microhenries for the Dynax configuration and 154 microhenries for the Philips
configuration; both loops demonstrated good frequency stability. The sensor profile in

32



Page 4

{LARGE HEAD PAN/FLAT HEAD SCREW:

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Figure 7: The sensor rests on top of the
screw heads

Vaera-)|-
> S787

beneficial to place a kerosene (‘torpedo’) type heater by -

the slot to gently warm the road surface. If multiple
sensors are being installed at the same time, now is a
good time to start heating up the channels, to give more
time to heat each individual channel. Clean the sensor
with a non-petroleum based solvent such as isopropyl
alcohol and place the sensor next to the cut channel.
The heater may be kept in place, but do not allow it to

get too close to the sensor and lead wire; just a gentle ©

warming is suggested. If using screws, insert the sensor
into the slot so it rests on the screw heads. Adjust the
Screws so that the sensor top is resting just above the
Toad surface. The mounting bracket, side ‘A’ (Figure 8)
should be used as a guide. For areas with snowfall and
snowplows, side "B’ of the mounting bracket should be
used as a guide.

If using the
mounting brackets, mount the brackets onto the sensoOr
(see Figure 9) using the cable ties. In areas without
snowfall, use side °A’ of the bracket. This will allow
for the sensor to be mounted slightly proud of the road
surface, giving the sensor that maximum impact from
vehicles. In areas of snowfall, it is recommended that
the sensor be mounted flush with the surface of the road.
In this case, use the flat side (side "B’) of the mounting
bracket in

MOUNTING BRACKET

HOLE FOR CABLE TIE
SIDE \
Cc
SIDE aN

NOTCHED SIDE

Figure 8: Side ‘A’ is against the sensor
for norma] installation; Side “B? is used in
snow areas.

Figure 9: Cable ties are used to hold the
sensor to the mounting bracket

some damage.

8 contact with the
MOUNTING BRACKET top of the sensor.
TAPE Three brackets
CABLE TIE should be used
SENSOR for each sensor;
EPOXY. \ one about 6°
from each end,
‘4ag>e SSg74-,| and one in the
->b 44 - 9 fi middle of the
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sqz,| Sensor. Note - it is preferable to mount the sensor just
v

above the road surface for higher output, if mounted
level, the outputs will be lower.

If there is some minor curvature of the road, the sensor
may be GENTLY bent (see Figure 10) to conform to the
curvature. WARNING: This should normally be left to
experienced personnel as too much bending may cause

El Atochem Sensors inc, PO Box 799, Valley Forge, PA 19482 © (215) 666-3500 Fax (215) 666-3509



2.3.8 Golden River Limited

GRI installed a Marksman 660 classifier with Traffic 2000 (14 mm width version)
piezoelectric axle sensors and one four-turn loop. The axle sensors are a domed type that
extends slightly above the road surface. The sensor layout is shown in Figure 17. The
Tutting was 5/32 inch at the location of sensors 1 and 6/32 at the location of sensor 2. The
installation was performed on 1/13-14/93. The weather was partly cloudy and 58° F on the
13th, partly cloudy and 47° F on the 14th.

The general axle sensor installation procedures were followed. The sensor slot was
cut for snug fit (Imm clearance on each side of the sensor) using ganged blades on the
asphalt saw. Each end of the cut was made a little wider and deeper to protect the ends
of the installed sensor. The slots were cleaned then dried and preheated with torpedo
heaters. One layer of duct tape was placed along the top of the slot leaving approximately
1/4 inch of pavement next to the slot uncovered because of the domed sensor construction.
The epoxy used was Traffic Coil which was poured in sufficient quantity such that excess
material extrudes around the sensor. The excess is trowelled off, and the sensor surface is
cleaned with acetone. No weights are required for this type of sensor, it is simply pressed
down until the domed portion is touching the pavement. The epoxy had been preheated in
a heated truck cab for two hours before mixing, and cured very quickly under ambient
conditions. The vendor replaced the leading sensor the next day because it was decided that
better performance would be achieved with the axle sensor nsuch nearer to the loop than
first installed.

‘The installed sensor element profile shown in Figure 18 shows that the domed
portion of the sensor extended above the road surface approximately 0,12 inches. Since the
sensors were flexible, good conformity to the rutting profile was achieved.

Loop measurements indicated 136 microhenries and good stability. Initial tests of
the axle sensor with oscilloscope indicated outputs slightly lower than desired by the vendor
and somewhat erratic. Both sensors were replaced on 3/11/93 (55° F and partly cloudy)
using the same installation procedures. The sensor output was better, but the classifier was
Dot giving consistent results. The equipment was returned for checkout and repair, but was
not working properly in time for the first evaluation. The equipment was then returned to
GRI in Great Britain for checkout and repair, and was functioning properly for the second
evaluation.

36



*Plezo-Electric
Data Sheet No. 1

Specification
Sensor dimensions
Section widths: 12%, 14*, 16, 18*, 20mm _(° available ex stock)
Depth: to suit 25 mm minimum slot depth
(Other sections can be supplied to customer specifications.)
Lengths: 2, 25, 3,35, 4, 5,6, 7, 8 9m. (Other lengths to order.)
Plezo-electric cable

Piezo-clectric polymer: polyvinylidene fluoride (PVDF or PVF2)
Piezo-clectric coefficient: 3pCiN at 23°C

Capacitance: 850 pF/m

‘Temperature range: =40to +70°C

Features: A robust and close-tolerance transducer which provides reliable and repeatable signals over a
wide temperature range. It is self-screening, and has a proven performance in many environments.
Signal cable

4mm diameter co-axial cable - see Data Sheet No. 15 for full specifications.

Its joint to the piezo-electric cable is carried within the rubber casing for maximum protection from
mechanical

damage, and specially matched splicing components are used to ensure the most reliable
connections. Ten metres of signal cable are provided with the sensor assembly: other lengths on request.

Typical sensor output characteristic:

12000 Charge output as a function of pressure

10000
charge
©C) 6000
4000
2000
oo —T > r
20 40 60 6&0 100
Pressure (bar)

‘The information in this Data Sheet is believed to be correct. Intending users should carry owt their own tests to establish
‘suitability (or their application. TRAFFIC 2000 LAATED will not be fisble for consequential damage arising from the use
Of these products. In line with our policy of continnous product development TRAFFIC 2000 LIMITED reserves the right

‘wo amend specifications and prices without prior notice.

Page 2 Mar.3992



5. CLASSIFIER RESULTS
5.1 OVERVIEW OF GENERAL RESULTS

In Section 5.2, the results of the comparison of the individual vehicle-by-vehicle
classifier outputs to the ground truth (from videotape) data are presented and discussed.
The results will be discussed for each of the two 48-hour testing sessions. The results
presented here include classification, axle spacing measurement, wheelbase measurement,
and overall length measurement accuracy. The results for the whole tests as well as the
parametric results versus percent trucks, air temperature, and pavement temperature are
presented for each classifier.

In Section 5.3, the parametric results versus percent trucks, air temperature, and
pavement temperature are summarized for all the classifiers and tests. General trends of
performance are presented and discussed.

5.2 TEST RESULTS FROM INDIVIDUAL CLASSIFIERS
The results of each classifier model and sensor configuration for each of the two 48-

hour tests are presented in the following subsections. The overall classification matrix for
each is depicted as well as table demonstrating the parametric results.

65



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2nd 48-Hour Test
127

20089
8342
1887
163
19625,
6408
31

386

59
Classification Matrix for TimeMark Delta II

Monmbinstions:

‘tri styped:

Wsensor err:

Wextra Vend:
Missing Vend:
*orrect:

mat
‘#verdor:
#splits:

Figure 52.



Table XX. Accuracy Summary for ECM HESTIA
2nd 48-Hour Test

% Tracks
0-20 06.55 099 943 0.508 | 1349 | 2232 2.910 11562 | 1639
20-40 07.00 TAD 94.4 0.403 | 1.548 | 2229 3,130 | 113.14 | 15.48
40-60 05.08 79.2 94.8 0.252 | 1.874 | 2.174 4.127 | 109.35 | 14.43
Air Temp
60-69 05.03 05 93.7 0.449 | 1.496 | 2310 3.059 114.86
70-79 06.11 72.0 94.1 0.429 | 1392 | 2.193 3.116 | 11421
80-89 10.17 74.4 96.3 0.457 | 1.904 | 2.186 2.942 113.78
Pav Temp
60- 69 3.43 69.6 93.6 0.383 | 1.198 | 2.335 3.296 115.65
710-79 5.26 BA 943 0.423 | 1.748 | 2246 3.141 113.39
80- 89 5.98 T34 94.3 0.420 | 1.292 | 2223 3.010 114.01
90- 99 6.91 TLS 94,0 0.452 | 1282 | 2259 2.883 114.59
100-109 8.76 723 94.5 0.460 | 1646] 2.122 3.280 114.06
110-119 741 67.7 95.7 0.515 | 1617 | 2.160 2.506 116.58
fa hora Se

120



ee ee ee ee ee ee ee



5.2.8 TimeMark, Inc. Delta I

The TimeMark, Inc. model Delta Hi classifier used a P-P sensor configuration with
Philips Vibracoax piezoelectric axle sensors. The results of this classifier are presented

below.
5.2.8.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 50. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 78.9% of the vehicles (94.4% if class 2-3
errors not included). The number of vehicle axles was miscounted 2.83% (percent sensor
errors) of the time. Approximately 1.3% of the vehicles classified by the Delta II were the
result of a suspected split or combination.

There were more than 3600 vehicles missed (see "#Missing Vend:" in Figure 50) by
this classifier that were recorded on video tape. Most of the other vendors (with no gaps
in recording time) missed less than 2000, most of which can be accounted for by lane
changes. By reviewing binned data for this classifier and the ground truth data, it was found
that roughly half of the class 2 and 3 vehicles were missed by this classifier. Apparently, the
sensitivity of the sensors and classifier electronics was not sufficient to detect a large number
of the passenger cars and small trucks. While the classification accuracy of those detected
was fairly good, a large number of vehicles were missed by this unit.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 51. The TimeMark classifier measures axles spacings and wheelbase length. The
measurement error Statistics (mean and deviation) for all measurements are included in the
figure as a function of measured vehicle speed (mph). Note that all measurements are in

feet.

Table XXII contains a summary of the results of the classification accuracy as a
function of percent vehicles with greater than two axles, air temperature and pavement

temperature.

122



The classifier was installed in the cabinet and the sensors were connected. After
making the normal internal adjustment of sensor threshold for a new installatian, the system
was working properly and was approved for evaluation. On a later visit, the vendor replaced
the EPROM with updated version and readjusted the sensor threshold.

40



ee Me ee ee a ee ae a

EXECUTIVE SUMMARY

In this project, a number of vehicle classifiers were tested to determine their accuracy
in classifying vehicles into the 13 FHWA vehicle classes, in measuring axle spacings, and in
Measuring overall vehicle length. The scope of the project was limited to commercially
available equipment that was available in September 1992. The objectives of the project
were to:

e Determine the adequacy of vehicle counting devices.

e Determine the adequacy of various types of equipment to correctly sort
vehicles into the 13 FHWA vehicle classes (as identified in the FHWA Traffic

Monitoring Guide).
e Determine the adequacy of automatic measurement of overall vehicle iength.

e Determine how the vehicle and axle sensor technology affects the accuracy of
the vehicle classification.

e Determine the effects of vehicle repetitions, heavy axle loadings, and weather
on pneumatic tube axle sensors and other types of vehicle and axle sensors.

A total of 13 sensor and classifier configurations from 10 equipment vendors were
installed from December 1992 to April 1993 on the west bound side of I-20 near Covington,
Georgia (30 mi. east of Atlanta). They were all installed in a single lane for side-by-side
comparison.

All of the classifiers tested (excluding the one used for the pneumatic tube tests) used
a combination of magnetic loop detectors and piezoelectric axle sensors, Although a wider
variety of sensor technologies were desired for the project, none of the vendors using other
sensors responded to the FHWA request for participation with commercially available
equipment. A majority of the participating vendors used a P-L-P (piezo-loop-piezo) sensor
configuration in the roadway, while the remaining vendors used either a P-P or L-P-L sensor
configuration.

Three tests were conducted in order to fully characterize the performance of the
classification equipment. Two 48-hour tests were conducted on May 5-7, 1993 and
September 9-11,1993. These tests provided comparison of the vehicle-by-vehicle data from
the classifiers with ground truth data obtained from a video tape of the traffic stream in the
test lane. The classifiers were assessed to determine their classification accuracy, and their
ability to accurately measure axle spacings and overall length. The performance of the
classifiers was assessed parametrically versus the percentage of vehicle with more than 2
axles, the air temperature, and the pavement temperature.



2

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Classification Matrix for Diamond TT-2001

(Autologger) 2nd 48-Hour Teast
5

Figure 66.



2 AUGMENTED PNEUMATIC TUBE TEST

An augmented pneumatic tube test was conducted during the second 48-hour test.
A Peek 241 (TrafiCOMP III) was configured to monitor both westbound lanes of traffic
using pneumatic tubes. One pair of tubes covered the near lane (same lane as used for all
other tests), and one pair of tubes were placed across both lanes of traffic.

The goal of the test was to determine how accurately the classifier could count
vehicles and axles in two lanes at the same time. Obviously, the second set of tubes would
detect axles in both lanes of traffic simultaneously. The goal of the test was to determine
if the lanes of traffic could be separated and counted accurately.

The Peek 241 was intended to be configured to record and bin the separate lanes of
traffic. Unfortunately, the classifier was configured to sum both lanes of traffic into one bin.
The resulting data file had all vehicles in the near lane counted twice and the far lane
counted once. This format adds to the ambiguity of the counting if one lane or the other
has an error and thus would not be a fair test of the pneumatic tubes to count vehicles and
axles.

It is recommended that this test be repeated in the future. The test should be

conducted either with two separate classifiers, or with one classifier configured to store the
results of each pneumatic tube pair in separate bins.

183



PEEK TRAFFIC, INC.
1500 North Washington Blvd.
Sarasota, FL 34236

SALES REPRESENTATIVE
Jim Stemitz (813) 366-8770
FAX (813) 365-0837

MODEL NAME
TrafiCOMP Tl Model 241

GENERAL DESCRIPTION OF EQUIPMENT
Multi-lane vehicle classifier. Operates in binning mode, up to four lanes
classification or eight lanes of volume. Available with inductive loops,
Piezoelectric sensors, or road tubes. Equipment also operates with other
sensors which provide a contact closure.

METHOD OF OPERATION
Unattended, capability to access data via telemetry is standard.

METHOD OF DATA STORAGE
Battery-backed RAM.

DATA STORAGE CAPACITY
64K Standard.

VEHICLE CLASSIFICATION SCHEME
Up to 15 bins.

POWER SOURCE
6 Volt 10 amp-hr battery, can be powered by AC source or solar power
depending on the options selected.

OPERATING TEMPERATURE RANGE
-40°F to 158°F (Electronics)

OPERATING VEHICLE SPEED RANGE
5 to 80 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
6.5" x 9.5" x 10" cast aluminum housing - 15 lbs

MAXIMUM LENGTH OF LEAD CABLE
Approximately 800 feet

PURCHASE COST OF EQUIPMENT
$1,475 to $3,000

207



5.2.10.3 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XXX. The totals for the
entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the

first and last of the seven days.

Table XXX. Long-Term Count/Classification Accuracy
IRD TC/C 530-4D/4P/4L (P-L-P)

Total Total Last Day
_ Gmd Truth Difference Percent
i 102.54 103.44
100.91 N/A
I 92.86 120.00
| 76.42 TAB
225.98 208.79
|| 200.00 171.78
Class 5 1855 794 1061 127.27 246.48
Class 6 N29 680 49 106.12 103.33
Class 7 “9 2 -15 60.00 50.00
Class 8 832 1191 -359 82.63 15.23
Class 9 i 9627 7411 2216 129.52 130.14
Class 10 107 1690 +1583 637 5.23
Class 11 242 370 -128 60.00 65.22
Class 12 67 94 27 80.00 R22
Class 13 IL 0) 191 -191 0.00 0.00
Class 15 0 oO 0 -
148



the test site were removed from the ground truth data for detailed vehicle-by-vehicle
comparison (48-hour tests). Those which entered the test site after the pole camera were
already not included in the ground truth data. The program for aligning and comparing
ground truth data to classifier data ignored all vehicles in the classifier’s data which did not
have an appropriate match (in time) in the ground truth data.

The vehicles which changed lanes were identified using the video tapes from the lane
change camera located on the overpass at the end of the test site. The tapes were viewed
on a VCR and monitor (left side of Figure 22) an the time and class of each vehicle that
changed lanes was manually recorded. The classifier over which the vehicle began and
ended its lane change, and the direction of the lane change (in, out, both) was also
recorded. Lines were drawn on the monitor screen to identify the locations of the
classifier’s sensors to enable the user to locate the classifier locations when viewing night
time footage of the video tapes. The vehicles identified as leaving the test lane after the
video monitoring area (pole camera) were manually removed from the ground truth data
for the detailed analysis of the 48-hour test data.

For the long term statistics of the 7-day test, the lane changes were ignored. It was
impractical to try to identify and remove lane changing vehicles from the classifier’s binned
data. The problems with removing the vehicles included identifying the particular classifiers
for which the vehicle needed to be removed, and determining the effects of vehicle which
had partially changed lane when passing over the classifier’s sensors.

A review of the number of lane changes in a typical day (in the first 48-hour test)
revealed the following:

1. Number of vehicles leaving the test lane = 384.

2. Number of vehicles entering the test lane = 408.

3. Number of vehicles which both entered and left the test lane = 90.
The number of vehicles entering and leaving the test lane are nearly equal, and the number
of vehicle entering and leaving the test lane was relatively small. The ADT for the first test
was approximately 9700 vehicles and the total number of vehicles which changed lanes was
882, Therefore, the percentage of vehicles which changed lanes was approximately 9.2%.
4.3. THE STANDARD DATA FORMAT

To reduce the number of programs required to handle the different storage formats

of the classifier vendors, the detailed vehicle-by-vehicle classification and measurement data

was converted to a standard format. Simple conversion programs were written by GTRI for
each vendor data format which would convert it to the standard data format. The ground

57



2.3. AVCSYSTEM INSTALLATIONS

A summary of each vendors’s installation configuration and specific installation
procedures, where they differ from the general installation procedures of Section Il, are

presented below. Any problems that occurred with the installation or with the initial system:

checkout are discussed. An overall view of the installation layout is shown in Figure 2. The
station numbers show that the test area extends from approximately station 183 to station
865 for a total length of 682 feet.

WKROS. ‘PEEK TRATIC ‘PAT EQUIPMENT MATRON SYSTENS
‘SYSTENS (CORPORATION, INC. CORPORATION
i =]
CONT.
BELOW
BLECTRONIC TMEWARK INTERNATIONAL ROAD COLDEX RIVER ‘DIAMOND UNE CHAE
(CONTROL MEASURE. WC. DYNAMICS, WC. TRAFFIC LAATED: WAFRC PRODUCTS CAMERA t
I > aan )
_ ~ eee eee ee ee eee - a7 seh tie
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C= 7 OL MI m3 i ROI 1
6 j i “SA ii
GA BI
OERPASS

Figure 2. Overall Layout of Evaluation Site

12

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1. Turn on the PC, change to the data reduction directory, and type "CVCRS
<return>". Enter the file name for storing the data at the prompt "Enter Work File
Name:".

2. Turn on the VCR and second monitor, insert a pole camera tape, and hit PLAY on
the VCR.

3. When the CVCRS reaches the main screen (showing menu options at the top of the
screen and vehicle data at the bottom), hit PAUSE on the VCR.

4. Select "Calibrate" on the CVCRS main screen. Follow the instructions to enter the
four comers of the calibration box on the pavement, and enter the length of the
calibration box (40 feet in this test).

5. Record each vehicle using the following steps:
a. Advance VCR tape and PAUSE when a vehicle is on screen.

Click the right mouse button to make a crosshair cursor appear on the second
VGA monitor superimposed on the video image.

c. Align the vertical bar of the crosshair with the front of the vehicle and click
the Jeft mouse button (position, of the horizonta) bar is unimportant).

d. Align the crosshair vertical bar with the center of the first axle, align the
horizontal crossbar with the bottom of the tire, and click the left mouse
button. Repeat this step for each successive axle.

e. _ Align the vertical bar of the crosshair of the rear of the vehicle and click the
left mouse button.

f. Click the right mouse button to exit the vehicle data entry and return the
cursor to the main CVCRS screen, The program will automatically read the

time from the tape.

6. Wf anerror is made in the vehicle entry, exit the data entry screen (click right mouse
button), select "Re-Enter Vehicle" from the main menu, and repeat step S.

7. If the vehicle is longer than a full screen, then use the following steps:

a. Pause the tape with the front bumper and at least half the vehicle displayed
on the monitor. '

55



5.2.9 International Road Dynamics, Inc. TC/C 530-4D/4P/4L (PR-L-PR)

The International Road Dynamics, Inc. Model TC/C 530-4D/4P/4L classifier was
tested with two separate sensor configurations. The first configuration used a PR-L-PR
sensor configuration using Dynax AS-400 resistive piezoelectric (PR) axle sensors. The
results of this classifier and sensor configuration are presented below.

5.2.9.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 54. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 69.3% of the vehicles (88.4% if class 2-3
errors not included). The number of vehicle axles was miscounted 8.89% (percent sensor
errors) of the time. Less than 1.3% of the vehicles classified were the result of a suspected
split or combination of an actual vehicle. This IRD unit missed a larger number of vehicles
than expected.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 55. The TC/C 530-4D/4P/4L classifier measures axles spacings, wheelbase length,
and overall vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XXV contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

131°



3.2.13

Problems and Exceptions to Test Procedures

There were no significant ‘Problems with the test equipment encountered during the

fre
first test.

ratire: ere recorded manually every 1§ minutes

The — a
The air and pavement temperatures were recoraea

using a thermocouple and hand-held meter.

The problems experienced with the participating vendor’s equipment during the first

48-hour test are as follows:

- This systems had a software bug in the TELCOM

Mikros Systems TEL-2CM
_ software used to download data to the PC. The download utility skipped the

data stored in certain portions of the classifier memory when downloading to
the PC. This resulted in gaps averaging one gap every 2 hours that ranged in
time from 16 minutes to over 2 hours. This problem was fixed after this test
with a TELCOM software upgrade from the vendor.

Peek TrafiCOMP Il - Twice during the test, the classifier’s processor halted
and the equipment stopped classifying vehicles. The gaps totalled about 3
hours and 26 minutes. To restart the processor, the cover of the unit had to
be removed and the processor reset.

Peek GK-6000 - This classifier required periodic downloads to a PC to store
data. During these downloads, the classifier didn’t record traffic data. The
downloads took generally greater than 15 minutes.

Electronic Control Measure HESTIA - New PC software received from the

vendor prior to the first 48-hour test was incompatible with the firmware
installed in the classifier. The classifier could not be set up at the beginning

fect with the new enfiware The vendor cent the old <atnware

- of the test with the new software. The vendor sent the old software by

express Courier and the classifier was started approximately a day late. The
system also locked up once during the test and lost about 8 hours of data. A

full reset was required to restart the equipment.

TimeMark Delia IJ - A 1 MB memory card installed in the classifier was not
recognized by the unit. The unit continued to classifier until the internal

memory was full and then stopped recording vehicles. The result was that the
final 18 hours of the first test were not-Tecorded by the unit.

i - The processor in the
classifier seemed to lock up occasionally. Some time the unit returned to
normal operation on its own, but other times the unit had to be stopped and
restarted in order to correct the problem. The data showed gaps in the lane
1 record only corresponding to these down times. The vendor updated the
firmware (ROMs) in the unit after this test to correct the problem.

48



ee

2. EQUIPMENT INSTALLATION
2.1 EVALUATIONSITE

The objective of this project is to determine various accuracy parameters of
classifying equipment under as nearly idea) conditions as practical. An evaluation site was
needed that would accommodate installation of the test devices and equipment cabinets, a
mobile office for test personnel, and test instrumentation. The site should also have
minimal impact on the accuracy of the equipment under test. The GaDOT provided GTRI
with a number of candidate sites for testing with characteristics that meet the specifications
listed below, and a final selection was made by a consensus of GaDOT, GTRI, and the

ELTWa

rowaAa,
2.1.1 Evaluation Site Specifications
The specifications for the evaluation site are listed below.

A. Horizontal curvature of the roadway lane for 150 feet in advance of and
beyond the sensors shall have a radius of not less than 5,700 feet measured
along the centerline of the lane; .

B. A longitudinal gradient of the road surface for 150 feet in advance of and
beyond the system sensors shall not exceed 2 percent;

Cc. The cross-slope (lateral slope) of the road surface for 150 feet in advance
of and beyond the system sensors shall not exceed 2 percent;

re)

The width of the roadway lane or lanes being monitored shall be between

10 and 12 feet;

E. The pavement surface will be relatively smooth and free of rutting and
cracking; and

F. The traffic normally operates in a free flow condition of greater than 30
miles per hour and no more than 65 miles per hour.

2.1.2. Site Lecation and description

The selected site is located on the westbound side of I-20 east of Covington,
Georgia (30 miles east of Atlanta). There are two westbound lanes, but the testing is to
be conducted only in the outside lane. The roadway is straight; the grade is less than 1%
(westbound is uphill); the cross slope is negligible, and the lane width is 11 feet. The
speed limit is 65 MPH, and traffic backups rarely occur.



2.3.4 MITRON Systems Carporation

Mitron installed a model MSC 3000, single lane classifier with two Autologger-Gates
piezo cable Mini Replaceable axle sensors. These sensors consist of a channel which is
epoxied into the road and a replaceable sensor element. The channe! has a short section
of copper conduit on one end to which 3/4” plastic tubing is attached to form a conduit
from the channel to the edge of pavement for the coax cable. The sensor layout is shown
in Figure 9. The rutting at the location of both axle sensors was 9/32 inch. The installation
was performed on 12/7-8/92. The weather conditions were: overcast, light rain (in the
morning), and 42° F on the 7th; partly cloudy and 43° F on the 8th.

The channel was installed much like a typical piezoelectric sensor, and the general
axle sensor installation procedures were followed. In order to get the maximum cure time,
the slots were cut one day then filled with sand. The next morning the slots were cleaned
then dried and preheated with torpedo heaters. Two layers of duct tape was used along the
top of the slot. A strip of duct tape was also used on the top of channel to keep epoxy out.
The epoxy used was E-Bond G-100. The channels were installed using 16 leveling plates,
and since the channels were slightly flexible, good conformity to the rutting profile was
achieved. Epoxy was poured to fill the slot approximately half full. The channel was placed
in the slot and seated so that the leveling plates were in contact with the pavement. A new
empty caulk tube was filled with epoxy, and using a manual caulk gun, the voids along the
sides of the channel were filled. The epoxy was then smoothed with a putty knife. Since
the ambient temperature (43° F) was too low for efficient curing of the epoxy, the sensor
channels were cured using torpedo heaters.

The next day, the sensor element was installed in the channel. The protective tape
is removed and the channel is thoroughly cleaned of any debris. The sensor element is laid
out along the channel, and the coax is fed through the conduit. Each end and the middle
of the sensor element is initially seated in the channel then the element is hammered in
place with a rubber mallet. The sensor is very tight in the channel, but several screws are
used to ensure the element is held in place. The screws are countersunk in the channel and

the heads are covered with caulk.

Initial tests of the axle sensor with oscilloscope indicated outputs slightly lower than
desired by the vendor. The first set of elements were damaged by snow plows as well, and
were replaced on 2/11/93. The replacement procedure involved removing the screws and
pulling up the sensor element then installing a new one as before. The coax on one of the
replacements was very difficult to feed through the conduit, which probably should have
been a little larger.

Classifier installation, checkout and training were completed on 2/11/93. The vendor

indicated that the classifier was functioning properly but the new sensor output levels were
still too low for accurate operation. Thin shims were placed under both sensors to raise
them higher above the road surface. The vendor verified that the system was ready for

22



axles Spacing Statistics Length Statistics

Speeds Wean = STD. Veh = Axle_Spacings Speeds wean = STD Vehicles
8.598 10.973 4 3 <0 36.280 11.961 4
8.026 2.622 5 20 30.0-34.9 40.598 7.754 5
0.284 2 5 35.0-39.9 4.155 5-315 2
0.614 3 Ba 40.0°64.9 4.882 15.566 13
0.165 BRB 135 45.0-49.9 -0.987 17.623 B
0.186 ai? 853 §0,0-54.9 0.208 14.791 ai?
0.171 1677-3172 $5.0-59.9 -0.299 13.708 1677
0.132 392907449 $0.0-64.9 0.642 12.733 3929
0.106 38035814 $5.0-69.9 1.806 9.533 3803
0.084 1567 1926 70.0-74.9 -2.206 7.251 1567
0.091 2860339 75.0-79.9 -1.559 7-682 266
0.197 0.189 3B 38 »80 4.580 11.716 38

‘Overall <1,156 11.423 11814

0.139 0.726 11814 19789

Wheelbase Statistics Length Percentile Statistics

Speeds Mean = STD Vehicles Speeds ean = STD Vehicles

<0 27.945 18.014 4 218.95 136.20 4
30.0-34.9 5 34.9 250.692 84.361 3
35.0-39.9 2 425.312 28.191 2
40.0-44.9 3 86.545 3
45.0-49.9 B B
50.0-54.9 417 417
55.0-59.9 1677 1677
60.0-64.9 3929 3929
65.0-69.9 3803 ‘3803
70.0-74.9 4567 1567
T5.0-79.9 -0.108 1.445 286 a 685 37.820 286

>80 0.197 0.189 38 »80 86. 18.35 ed

Overall 0.232 1.781 11814 52.81 11814

Figure 59. Measurement Accuracy Versus Speed (MPH
)
IRD TC/C 530-4D/4P/4L (P-L-P) ~- lst 48-Hour Test

142



THERMOCOAX NORCROSS

While mixing with an electric drill, the temperature rises - check that
temperature stays below 100°F. The optimum temperature is 90°F. The
temperature can be checked with a handhoid thermometer (e.g., Mode! HH-21
from Omega Engineering, Inc.) :

While curing, the inner epoxy grout rises due to the exothermic chemical
reaction. If the mixed grout is left too long in the container the temperature can
tise too much leading to possible damage on the extension cable or the
impossibility to pour the grout in the siot.

Pour the grout to fill the slot up to half its depth. Install the sensor flush to the
top surface of the road, none of the aluminum channel protruding, (e.g., the
channel a little bit below the top surface of the duck tape, in the middle of the
slot). Be sure that all the sensor's bottom is resting in the epoxy grout and that
there is no air pocket underneath the sensor. Lay the extension cable in its slot.

Completely fill the slot with the grout avoiding air bubbles. Level the top !
surface of the grout with a tongue depressor trial or equivalent. After the grout
is mixed (Step 7) the grout must be poured inside the slot (Steps 8 & 9) as fast
as possible to avoid the sand to settle down to the bottom of the container and
the slot.

Allow the grout to cure. In cold weather it is possible to shorten the curing
time by gently heating the pavement and the grout with hot air. Be careful not
to overheat and damage the extension cable. The surface temperature of the
grout must remain below 110°F. Route the extension cable in its slot and seal
it with a conventional magnetic loop sealant.

When the grout is cured (hard enough not to move when a strong pressure is
applied to it) cut the hanging wires and remove the holding fixture and duck
tapes. The top surface of the grout can be smoothed with a grinder.

After routing and connection of the extension cable, check the integrity of the

sensors. Remove traffic signs and allow traffic on the lane. Check the voltage
generated by vehicles over the sensors. The actual reading will depend on the
voltmeter model. For a truck, the reading should be around 100 mV.

AUTHOR: GB PAGE: 5/5

CODE: VB 901 D 003



- DIAMOND TRAFFIC PRODUCTS

0.15

Sensor Heights (inches)

1

2 3 4

5

Distance from Solid Line (feet)

Figure 20.

Diamond Axle Sensor Profiles

42



- Step 3:

- Step 4:

- Step 5:

- Step 6:

- Step 7:

For installation with one Vibracoax sensor and two (2) ioops, the sensor must
be approximately 1 ft ahead of the second ioop.

For installation with one loop and two (2) Vibracoax sensors, the sensors can
be placed very close outside the oop. For optimum placement of the sensors,
consult the electronic instrument manufacturer.

Cutting of the grooves with a diamond blade saw (see drawings}. The depth of
the groove is 2". It is critical that the grooves are as straight as possible,
parallel each other and perpendicular to the axis of the lane. The groove for the
extension cable must be in the center of the sensor's grooves and at the same
depth.

Remove the pavement material between the grooves with a chisel and hammer.
Particularly in asphalt pavement be careful that the slot width is not larger

at the top than at the bottom. Ciean and dry the slot with compressed air.
Check with a sensor that the slot is large enough to accommodate the sensor
with at least 1/8" clearance in all directions.

Without a sensor inside the slot, finish to dry the pavement with hot air or a
gas burner. in cold weather it is recommended to reheat the pavement, on
approximately 6 inches on each side of the slot, up to 90°F (the human body
temperature is 99°F, the pavement will feel warm but not burning). With
asphalt pavement be careful not to overheat and burn the asphalt to keep a
good adherence with the grout.

Apply a layer of duck tape around the slot to keep the pavement surface clean
after the installation is finished. Clean the sensor aluminum channel with an
organic solvent or alcoho! to achieve a good adherence with the grout. Hang
the sensor from holding devices (3 to 4 per sensor) via copper wires.

Grout preparation - Whichever brand is selected carefully read the product data
sheet and instructions. Most popular brands are: E-bond G-100, Concresive
Paste epoxies and IRD methyl metacrylate. All grouts contain sand and must be
thoroughly mixed and homogenized, Quantity is approximately 1.5 gallon
{26lbs) for 6 ft. sensor and 3 gallon (52 Ibs) for 11.5 ft sensors. It depends on
the exact slot size. Temperature is an extremely critical factor for epoxy resin.
If too cold, it requires a long time to cure. If too hot it starts to cure in the
container or can exhibit cracks when cured. For E-bond, resin components
must be at least 80°F before mixing.

F1002

THERMOCOAX NORCROSS

| AUTHOR: GB PAGE: 4/5 }

te)

CODE: VB 901 D 003 REV:



2.2 GENERAL INSTALLATION PROCEDURES

All vendor sensor configurations included in-pavement axle sensors and, in most
cases, in-pavement loops. The GaDOT was responsible for providing the equipment,
tools, and labor for installing the equipment and was also responsible for traffic control.
GTRI monitored and documented the installation process with videotape and written
records. The sensors and equipment were installed in strict accordance with the
procedures recommended by the vendor, and each vendor sent a representative to
supervise the installation, The general procedures presented below were typically
followed by each vendor; any exceptions for specific vendors are noted in Section IV.

It was desirable to install the vendor configurations as close together as possible
to minimize the overall length of the test area. However, a concern was raised by
several vendors about possible electromagnetic crosstalk between their loops the loops of
other vendors. Without sufficient separation, a long truck may occupy two vendor’s

- loops simultaneously and induce crosstalk through the truck body. To avoid any
potential problems, the spacing between different vendor’s loops was maintained at 60
feet or more.

Individual locking equipment cabinets were pole mounted a minimum of thirty
feet off the roadway to house each vendor’s equipment and protect it from tampering
and vandalism. Ground rods were installed at each cabinet, and ground wires were
routed into the cabinets for the vendor’s use. Cable trenches were dug for the sensor
leads. Conduit was supplied for the sensor leads for each vendor who requested it.
Some cabinets were supplied with ac power for the classification equipment and for
portable computers used for data collection.

The installations were performed mostly during the winter months. Although cold

weather installations are not generally desirable. contra nal cchadule requirements
weather installations are not generally desirable, contractual schedule requirements

dictated winter installation for this evaluation. Fortunately, Georgia winters are not too
severe; the lowest temperature installation was at 38° F, and most were at 50° F or
above. The installation procedures included provisions for curing epoxy at low
temperatures.

2.2.1 Axie Sensor Installation

The following steps represent a typical installation of an in-pavement axle sensor.
These procedures were foliowed by each vendor except where noted in the detailed
installation descriptions of Section IV.

1. Decide on the approximate installation location (leading edge of loop to be
situated 60 feet west of the trailing edge of the last vendors loop).
Measure the rutting, and adjust the location slightly if necessary.

mm a me oF aw om me fw om os am an oe on fe ue



Table XXIM. Accuracy Summary for TimeMark Delta I

2nd 48-Hour Test

YY
Sensor | Correct | Correct | Axle | Axle
Errors {no 2,3) S.D.
Total 1,97
% Trucks
0-20 181 747 95.2 0.011 | 0.408 .

20-40 2.17 78.9 93.5 0.022 | 0.439
40-60 2.53 88.8 96.1 0.042 | 0.373

Air Temp
60-69 2.18 79.7 93.9 -0.027 | 0.404 .
70-79 1,79 76.6 948 0.018 | 0.423
80-89 2.53 76.4 94.6 -0.008 | 0.433

Pav Temp
60- 69 0.041 { 0.409
70-79 -0.015 | 0.407
80- 89 -0.019 | 0.464 .
90- 99 -0.019 | 0.403
100-109 -0.012 | 0.343
110-119 0.011 | 0.382

leasure Over: icle Ler
129



= a a Oo

ma ma ie ot we ee ee oe

—_ m= wz

5.2.2 Peek Traffic Inc. TrafiCOMP It

The Peek Traffic Inc. model TrafiCOMP II classifier used a P-L-P sensor
configuration and Philips Vibracoax piezoelectric axle sensors. The results of the individual
tests are presented below.

5.2.2.1 First 48-Hour Test

The classification matrix for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 30. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 75.3% of the vehicles (93.0% if class 2-3
errors not included). The number of vehicle axles was miscounted 3.71% (percent sensor
errors) of the time. Note that the TrafiCOMP II] output was not time stamped with seconds
and manual aligning of the data was required. Therefore, identification of splits and
combinations could not be accomplished.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 31. The TrafiCOMP III classifier measures axles spacings and wheelbase length.
The measurement error statistics (mean and deviation) for all measurements are included
in the figure as a function of measured vehicle speed (mph). Note that all measurements
are in feet.

Table V contains a summary of the results of the classification accuracy as a function
of percent vehicles with greater than two axles, air temperature and pavement temperature.

75



Table XXXII. Accuracy Summary for Diamond TT-2001
(Autologger) 1st 48-Hour Test

80- 89 !
90- 99 1.65 78.4 96.0 0.052 } 0.292} -1424 | 5.655 95.53 | 31.28 }}.
100-109 2.72 74.3 93.9 0.061 | 1,126 | -1.506 6.385 96.77 | 55.86
110-119 7.63 62.9 83.1 0.023 | 2.123 | 0.985 9.298 | 101.36 | 62.40
. =

157



2.3.6 TimeMark

TimeMark installed two classifiers (DELTA I and DELTA Il) each with one set of
two Philips piezoelectric axle sensors. The sensor layout is shown in Figure 13. The rutting
at the location of axle sensors 1 through 4 was 6/32, 5/32, 6/32, and 6/32 inch, respectively.
The installation was performed on 12/14/92. The weather was mostly cloudy with an air
temperature of 50° F.

The general axle sensor installation procedures were followed. The sensor slots were
dried using hand held propane torch being careful not to overheat the pavement. Two
layers of duct tape were used along the top of the slot. The epoxy used was Schul
International Ready-Set pavement grout (a technical bulletin is included in Appendix A).
Schul had a technical representative on site for the installation. The sensors were installed
using four leveling plates. Some difficulty was encountered in mixing the epoxy. One batch
cured too fast and did not allow time to completely fill the slot and smooth the epoxy, and
another batch cured in the bucket before adding the sand and had to be discarded. The last
batch was mixed for a shorter time before adding sand. This batch had a better working
time allowing for a smooth installation, and was used to top off and smooth the other
sensors. However, it also took much longer to cure, and about 2 hours before the lane
opened, a torpedo heater was placed on the sensor to speed curing. When the lane had to
be opened, that epoxy was still slightly soft. The sensor profiles in Figure 14 show that in
the wheelpath the sensors were all slightly high (up to +0.1 inches) and outside the
wheelpath they were all slightly low (up to -0.07 inches).

The axle sensors were tested with an oscilloscope. The outputs from sensors 2 and
3 were acceptable, but the output from sensors 1 and 4 were very low. After failing to get
sufficient output levels from sensors 1 and 4, it was decided by the vendor to abandon them
and only use sensors 2 and 3. The Delta 1 was withdrawn from the evaluation, and the
Delta II was connected to sensors 2 and 3.

The Delta I experienced an oscillation problem (continuous axle counts with no
vehicles present) and was repaired at the vendors facility. In order to get more consistent
signals for vehicles outside the wheelpath, bituthane tape was placed over the low spots on
both sensors. The classifier was then approved by the vendor for evaluation.

29



5.2.12 Second 48-Hour Test
The classification matrix for the second 48 hour test and the summary of number of

vehiclec frecl and vendor) michimed vehic! eencor errors. exvtra
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing

vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 28. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 63.5% of the vehicles (78.8% if class 2-3
errors not included). The number of vehicle axles was miscounted 4.81% (percent sensor
errors) of the time. Approximately 1.7% of the vehicles classified by the Mikros equipment
were suspected to be the result of a split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 29. The Mikros classifier measures axles spacings, wheelbase and overall vehicle
length. The measurement error statistics (mean and deviation) for all measurements, and
the overall length percentile statistics are included in the figure as a function of measured
vehicle speed (mph). Note that all measurements are in feet.

Table I contains a summary of the results of the classification accuracy as a function
of percent vehicles with greater than two axles, air temperature and pavement temperature.

70

_— eo oe Ph oe ee ce oe i a

= mm me



ma

INTERNATIONAL ROAD DYNAMICS INC.

CORPORATE OFFICE: 702 43rd Street East, Saskatoon, Saskatchewan, CANADA 87K.3T9
Telephone: (S06) 653-6600 Facsimile: (806) 242-5599

AS-475 AXLE SENSOR GROUT
- DIRECTIONS FOR USE -

GENERAL

IRD's AS-475 Sensor Grout is a resin based grout. Specifically designed to embed permanent ade
sensors in asphalt or portland concrete pavements.

The grout serves two purposes:
a) Adhesive bond between the sensor and road pavement material
b) Isolation medium between the sensor and road pavement.

AS-475 grout comes pre-mixed in convenient sized pails and is packaged in kit form to correspond
with the sensor type to be installed: AS-475-1 (20kg), AS-475-2 (15kg), AS-475-3 (5kg). The grout
consists of a resin material mixed with fine mineral aggregate. The aggregate provides strength,
consistency, and acts as a heat sink during the curing reaction (The curing of the resin liberates heat.
The sand absorbs excess heat to prevent the resin from cracking).

Curing of the grout begins once the catalyst (the white BPO-Benzoyl Peroxide Organic) powder has
been added. The reaction time for curing is dependent on external temperature conditions.
However the curing time can be controlled by adjusting the amount of BPO catalyst added to the
grout for various temperature conditions.

DIRECTIONS FOR USE

AS-475 grout comes with pre-packaged vials of BPO as follows:

AS-475-1 20kg 6 Vials, 33g each

{12 US quarts)

AS-475-2 15kg 3 Vials, 33g each + 3 Vials, 17g each
(9 US quarts)

AS-475-3 Skg 3 Vials, 17g each

{3 US quarts)

Depending on the installation temperature, you use either 1, 2, or 3 of the vials
per pail of grout. Working time (pot life) will be between 10 and 50 minutes.

MacDoc Spets.#39
ele ‘Rev & Fobra



Table XXXIV. Accuracy Summary for Diamond TT-2001
(Autologger) 2nd 48-Hour Test

60-69

70-79 10.73 11.2 12.1 0.225 | 0.552 | -3.802 3.632 93.43

80-89 6.86 0.3 03 0.096 | 0.243 | -3.415 0.775 95.83 1.00
| Pay Temp

f 60-69 | N/A N/A N/A | N/A | N/A] N/A | N/A | N/A | N/A
70- 79 | . 6.458 95.13 | 18.80
2.552 93.16 | 11.35
1.157 | 93.50 159
1305 | 95.01 1.82
0.000 0.00 0.00
pcecaectomecc)

161



INSTALLATION COST
Varies with users, type of road, and amount of sensors being installed.

NOMINAL INSTALLATION TIME
Depends upon experience of operator and type of sensors being installed.

INSTALLATION PROCEDURE .
Attach sensors, use computer to set up study.

SOME STATES CURRENILY USING THIS EQUIPMENT
Idaho, Maryland, Texas

OTHER COMMENTS

This unit can be purchased as a dual tube counter through 4 lanes of weighing
in motion.

198



188



on a 15-minute interval. During the second 48-hour test, the temperatures and rainfall
amounts were recorded using a PC interfaced to temperature sensors and 2 rain gauge.

At the end of the first 48-hour test, the classifiers, computers and video equipment
were stopped. Data was downloaded from the classifiers using a PC if needed and the
power was turned off to the equipment. All of the equipment was removed and returned
to storage where batteries were connected to chargers as needed.

At the end of the second 48-hour test, the classifiers were reconfigured to record
binned data on 15 minute intervals for the long-term (7-day test). The pole camera video
recorder was also switched to the extended play recording speed. The first two days of the
7-day test were the same two days used for the second 48-hour test, and the remaining 5
days were those immediately following the detailed test. The site was not continually
manned during the remaining five days of the 7-day test. Every approximately 5.5 hours,
the video tapes for the pole and lane-change cameras were changed. Temperature and

rainfall monitoring continued for the five davs as well.

monitoring continued for five days as

3.2. DETAILS OF INDIVIDUAL TESTS
3.2.1 First 48-Hour Detailed Test
3.2.1.1 Test Date and Conditions

The first detailed test session was conducted May 5 - 7, 1993. The air temperature
during the test ranged from 55 degrees F to 86 degrees F. "The pavement temperature
ranged from 63 degrees F to 118 degrees F. The weather was sunny and clear and there
was no precipitation during the test. This test was intended to be conducted under good

weather conditions as the a baseline for the remaining tests.

The traffic during the test was typical weekday traffic for the site. There was no
traffic congestion during the test and the average speed of traffic was typically near
65 MPH. The average daily traffic (ADT) in the test lane (as determined from the video
data reduction) was approximately 9700 vehicles.

3.2.1.2 Participating Vendors

The vendors and classifiers that participated in the first 48-hour test included all of
those listed in Table I except the Golden River Traffic Marksman 660. The Golden River
equipment was sent back to the vendor for repair and was not returned in time to be
included in this test. The Mitron Systems TEL-2CM was included in this detailed test, but
the Mitron equipment provided binned data rather than vehicle-by-vehicle output. All of
the remaining equipment either recorded individual vehicle records internally or were
capable of transmitting these records to a PC for storage.

47



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5.2.5.2 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 44. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 76.6% of the vehicles (95.1% if class 2-3
errors not included). The number of vehicle axles was miscounted 0.51% (percent sensor
errors) of the time. Less than 0.2% of the vehicle classified were the result of a suspected
split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 45. The PAT classifier measures axles spacings and wheelbase jength. The
measurement error statistics (mean and deviation) for all measurements are included in the
figure as a function of measured vehicle speed (mph). Note that all measurements are in

feet.

Table XVI contains a summary of the results of the classification accuracy as a
function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

106

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Table XLII. Overall Length Measurement Percentiles

(All measurements in percent of ground truth)

Equipment
Vendor

Sensor
Config.

48-Hour
Test #

Mean
Percent

Standard
Deviation

Mikros TEL-2CM L-P-L 1 108.43 26.62
Systems (Philips) 2 91.29 28.32
Peek Traffic, | TrafiCOMP P-L-P 1 N/A N/A
Inc. (Philips) 2 N/A N/A
P-P 1 N/A N/A
GK-6000 (Philips) 2 N/A N/A
1 N/A N/A
hits) 2 N/A N/A
AVC-100 P-L-P 1 N/A N/A
Equipmest {Atochem) 2 N/A N/A
Corporation, AVC-100 L-P-L 1 N/A N/A
(Philips) 2 N/A N/A
MITRON MSC-3000 P-P 1 N/A N/A
Systems DCP {Autologger) 2 N/A N/A
Corporation
Electronic HESTIA P-L-P 1 102.95 8.25
Control (ECM) 2 114.30 16.07
Measure t
TimeMark, Delta I P-P 1 N/A N/A
Inc. (Philips) 2 N/A N/A
International TC/C 530- PR-L-PR 1 9835 51.48 |
Road 4D/4P/4L (Dynax) 2 96.21 52.28
Dynamics, Inc. P-L-P 1 99.38 52.81
(Philips) 2 94.21 47.94
t
Golden River Marksman P-L-P 1 N/A N/A
Traffic Ltd. 660 (Traffic) 2 N/A N/A
Diamond TT-2001 P-L-P 1 97.62 45.35
Traffic (Autologger) 2 94.04 14,75
Products P-LP 1 95.06 14.46
sae 2
G

180



Table XVI. Accuracy Summary for PAT AVC-100 (L-P-L)
2nd 48-Hour Test

Air Temp

60-69 0.24 76.6 95.5

70-79 0.60 76.4 94.9 0.253 | 0.412

80-89 0.60 719 95.6 -0.193 | 0.403

Pav Temp

60- 69 0.27 763 94.8 0.327 | 0.382

70- 79 0.15 719 96.0 -0.269 | 0.428

80- 89 0.57 716 95.1 0.245 | 0.422 * . .
90- 99 0.73 159 95.1 0.250 | 0.425

100-109 0.72 759 943 0.223 | 0.426

110-119 0.64 T24 952 0.221 | 0.316

a “Does Not Measure Overall Vehicle Tength
109



2.3.2 Peek Traffic Inc.

Peek installed a model 241 TrafficComp I classifier with one set of sensors and a
model GK 6000 classifier with two sets of sensors configured as two lanes. The sensor
layout is shown in Figure 5. The TraffiComp uses two philips piezoelectric axle sensors and
one three-turn loop. The GK 6000 uses two philips piezoelectric axle sensors for each
configuration (loops were installed for the GK 6000, but were not used during the tests).
The rutting at the location of axle sensors 1 through 6 was 14/32, 15/32, 13/32, 14/32,
13/32, 12/32, respectively. The installation was performed on 11/23/92 (axle sensors 1-4
and loops 1-2) and 11/30/92 (axle sensors 5-6 and loops 3-4). The weather was partly
cloudy and 59° F on the 23rd, mostly sunny and 55° F on the 30th.

The general axle sensor and loop installation procedures were followed. The slots
were dried with compressed air, and the epoxy was cured under ambient conditions (no
heaters were used). Three layers of duct tape were used along the top of the slot. A strip
of duct tape was also used on the top of sensor; it was peeled off after the epoxy cured
resulting in a clean sensor surface. The epoxy used was Traffic Coil. The axle sensors were
pre-bent slightly to conform to the local rutting, and were installed using 4 leveling plates.
The resulting sensor profiles in Figure 6 show that all of the sensors were close to, or above,
the pavement surface level over most of their length. The worst case height variation for
any sensor is 0.2 inches (sensor 4).

The axle sensors were tested with an oscilloscope and were all working properly. The
loop used for the TraffiComp II (loop 3) measured 140 microhenries and demonstrated
good frequency stability. The other loops were functioning properly as well, but were not
used during the evaluations.

Classifier installation, checkout and training were performed on 3/24/93. The vendor
indicated that both classifiers were functioning properly and were ready for testing. During
a subsequent checkout of the TraffiComp Il, the processor board latched up several times
requiring an internal reset. The vendor supplied a replacement processor board.

16

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164

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15290

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Classification Matrix for Diamond TT-2001

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Figure 68.



TABLE OF CONTENTS (cont.)

3.2.2 Second 48-Hour Detailed Test ........---- esse eee ee eee 49
3.2.2.1 Test Date and Conditions ...........-+--6+- 49
3.2.2.2 Participating Vendors ........-----eereeeee 49
3.2.2.3 Problems and Exceptions to Test Procedures ... 49
3.2.3 Seven-Day Test ..... 00.6 epee reece cee n eter eteeeres 51
3.2.3.1 Test Date and Conditions ...........+------ $1
3.2.3.2 Participating Vendors .....-...+-+2+--eeees 51
3.2.3.3 Problems and Exceptions to Test Procedures ... 51
DATA REDUCTION AND ANALYSIS ........-00020ecereeeeeree 53

4.1 THE COMPUTER VEHICLE CLASSIFICATION AND
REDUCTION SYSTEM (CVCRS) .....-..--- sects eter nets 53
4.1.1 Hardware 2.0... cece eee cnet eee n ene 53
4.1.2 Software... 0. cc ccc eect e eet eeeeee ete 53
4.2. HANDLING LANE CHANGES ..........---e eee eee e rece 56
4.3. THE STANDARD DATA FORMAT 57
4.4 THE "BINNED" PROGRAM ........-:..ee eee e reer ter eeee 58
4.5 THE "ANALYZE" PROGRAM ............--e eee reer reece 59
4.6 TYPICAL ANALYSIS OUTPUTS .........- 5c eee cence eens 61
CLASSIFIER RESULTS ...... 0.2: cece e cece eect er eee teenies 65
5.1 OVERVIEW OF GENERAL RESULTS .........----++--+e0> 65
5.2 TEST RESULTS FROM INDIVIDUAL CLASSIFIERS .......... 65
5.2.1 Mikros Systems ........ 2.0 e cee eee cece een e eee e ene 66
3.2.1.1 First 48-Hour Test .......-. 2.00 eee ee ee eee 66
5.2.1.2 Second 48-Hour Test .........-.2 02 ee eeee 70
5.2.1.3 Seven-Day Test ..... 0.202 eee eee re ee ncee 74
5.2.2 Peek Traffic Inc. 1.1... eee cet etree teens 75
5.2.2.1 First 48-Hour Test ......-. 000s eee e ee enee 75
5.2.2.2 Second 48-Hour Test ........... 2.00 eee ee 79
5.2.2.3 Seven-Day Test ...... 20. e eee cece eee ee 83
5.2.3. Peek Traffic Inc. Gk-6000 2.0.2... c eee cece eee eee 84
5.2.3.1 First 48-Hour Test .........---- eee eee eee 84
5.2.3.2 Second 48-Hour Test ........---.- ee ee eres 91
5.2.3.3 Seven-Day Test 22... 0.0.2 c eee ee eee eee 98
5.2.4 PAT Equipment Corporation, Inc. AVC-100 (P-L-P) ........ 100
5.2.4.1 Seven-Day Test ....-...-- ese eee eee 101
5.2.5 PAT Equipment Corporation, Inc. AVC-100 (L-P-L) ........ 102
5.2.5.1 First 48-Hour Test ........ 2.6. ee cee eee eee 102
5.2.5.2 Second 48-Hour Test ............20--00e5- 106
5.2.5.3 Seven-Day Test 0.2.0.0... cee cece e eens 110
5.2.6 Mitron Systems Corp. MSC-3000 DCP ...........+----+5. 11k

x

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192



Axles Spacing Statistics

Speeds wean sT0 Veh = Axle_Spacings
<0 0.000 0.000 0 0
30.0-34.9 0,000 0.000 0 0
35.0-39.9 0.000 0.000 a o
40.0-44.9 0.100 0.644 1 4
45.0-49.9 0.137 0.320 10 22
50.0-54.9 0.139 0.356 ” 253
55.0-59.9 0.435 7.819 638 1638
60.0-64.9 0.089 0.662 2641 6366
65.0-69.9 0.072 0.592 2093 3834
70.0-74.9 0.059 0.351 877 1150
75.0-79.9 0.070 0.316 V3 122

>B0 0.002 0.339 42 42
Overali 0.124 2.791 6506 = 13431

Wneeibere Statistics

Speeds ean stD Vehicles
3 0.000 0.000 o
30.0-34.9 0.000 0.000 oO
35.0-39.9 0.000 0.000 oO
40,0-44.9 0.400 0.000 v
$5.0-49.9 0.302 0.380 10
50.0-54.9 0.386 0.540 vi
55.0-59.9 1.115 19.817 638
60.0-64.9 0.216 0.932 2641
65.0-69.9 0.132 0.756 2093
70.0-74.9 0.078 0.374 877
75.0-79.9 0.075 0.313 3
>80 0.002 0.339 42
Overall 0.256 6.258 6506

Figure 51. Measurement Accuracy Versus Speed (MPH)
TimeMark Delta II - ist 48-Hour Test

124



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DNmArs

Aluminum Channel 766 Poot)
\ Encapsulating Compound Connector |
X\
VIBRACOAX
' Hi HHH : i He EUR HIE
|. 4...

"| CLASS 1: 11.5 or 6Ft, CLASS 2:6Ft | 2: [1°
+

| 6 Ft Sensor : 6'4" ; 11.5 Ft Sensor : 1110"

PHILIPS VIBRACOAX SENSORS



Table XXVI. Accuracy Summary for IRD TC/C 530-4D/4P/4L

(PR-L-PR) 2nd 48-Hour Test

Pav Temp
60- 69
70-79
80- 89
90- 99
100-109

110-119

9.435

10.792
12.190
10.601

93.93
95.54

9762

45.03
53.79
56.03
53.78

138



Sensor Heights (inches)

0.15
0.10

0.10 £

0.00
-0.05

-0.15

0.20  ~|
0.25
-0.30 |
0.35 |

TIMEMARK INC.

oO

Figure 14. TimeMark Axle Sensor Profiles

31



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x
3
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wi
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YOSNA3S NVYHL HADNO1 .E

SLOT CUTTING (DIAMOND SAW)
2 inches

CABLE SLOT

SLOT PREPARATION

HOT AIR (PAVEMENT TEMP. 90 F)

CHISEL & HAMMER
DUCK TAPE

COMPRESSED AIR



INSTALLATION COST
Varies with users desire for enclosures and type of sensors

NOMINAL INSTALLATION TIME
10 - 20 minutes

INSTALLATION PROCEDURE
Attach loops or piezoelectric sensors/solar power (if used).

SOME STATES CURRENTLY USING THIS EQUIPMENT
Idaho, Washington, Florida, North Carolina, Michigan, Wyoming, Alabama,
California, Nevada, New York, Tennessee, Oklahoma

OTHER COMMENTS
Other equipment available from Diamond Traffic Products:

TT-501 - Whereas the TT-2001 will classify up to 4 lanes and count as many
as 8, the TT-501 is a less expensive, basic version that will ciassify only one
lane and count vehicles in two.

GTRI COMMENTS
Piezo-Loop-Piezo

194



DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
The Lambda unit is 14.5" long, 8" wide, 5" high, and weighs about 18 pounds
fully configured.

MAXIMUM LENGTH OF LEAD CABLE
The loop detector can handle inductance of up to 500 micro Henries and the

piezo detector can handle down to a 5 milliamp signal.

PURCHASE COST OF EQUIPMENT
The Lambda ranges from $1500 for a two road tube model to $2850 for four

road tube, eight loop, and eight piezo capability.

INSTALLATION COST
Installation cost will depend on the on-site enclosure, power capabilities,
communication options, and sensors.

NOMINAL INSTALLATION TIME
Once all the permanent items are in place it takes less than 10 minutes to
attach sensors and configure recorder for data collection.

INSTALLATION PROCEDURE
Connect sensors, power, and communications cables then go through menu
to set up for data collection.

SOME STATES CURRENTLY USING THIS EQUIPMENT
Information not available

OTHER COMMENTS
. The Lambda is in final testing phase and will be available by January 1994.
The loop detector has low current draw without sacrificing speed accuracy.
The piezo detector can be adjusted to amplify the signal as well as adjust the
sensitivity.

212

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nnermtrmtinma Pwe eS we ee wa eH ee

TABLE OF CONTENTS
59°02) 27 \ ©) iii
EXECUTIVE SUMMARY ........ 2. cece cece e reer e etree teen neeanee Vv
TABLE OF CONTENTS ........ cece ccc eee etree tenet eee nee nnee ix
LIST OF FIGURES ....... 02. ccc cette ce ee ete e renee tee neees xiii
LIST OF TABLES ...... 0... cece cece eee eter ence een ttre eee xvii
1. INTRODUCTION AND SCOPE 1
1.4. Background 0.0.0.2... 0. eee eee e eee eee eee t eee teee 1
1.2 Participating AVC System Vendors 2
2. EQUIPMENT INSTALLATION 5
2.1. EVALUATION SITE .... 1... ccc eee eter ee eee ees 5
2.1.1 Evaluation Site Specifications . eee ae 5
2.1.2 Site Location and description ... detec e eee 5
2.1.3 Test Facilities and Instrumentation ........---.+ eee eeseee 6
2.2. GENERAL INSTALLATION PROCEDURES
2.2.1 Axle Sensor Installation
2.2.2 Loop Installation .......- 0.02 eee eee ee eee .
2.2.3. System Testing .... 20.0... c cc cee ete ee ene
2.3. AVC SYSTEM INSTALLATIONS 12
2.3.1 Mikros Systems ........... 13
2.3.2 Peek Traffic Inc. .......-- :: 16
2.3.3 PAT Equipment Corporation 19
2.3.4 MITRON Systems Corporation ...........0- esse eee cere 22
2.3.5 Electronic Control Measure ....... 66. e cee eee eee ene 26
2.3.6 TimeMark 2.20.0... cece eee ete eee teen e tens 29
2.3.7 International Road Dynamics .............--+ eee eeeeee 32
2.3.8 Golden River Limited ....... 0.02 e eee ene tee eee eee 36
2.3.9 Diamond Traffic Products .........0 6 ees eee tener eeee 39
2.4 INSTALLATION SUMMARY AND CONCLUSIONS ........... 43
3. TEST SESSIONS ee eee eee eee eee eee e et eee tenes 45
3.1 OVERVIEW OF TEST PROCEDURES ..........--se eee eeeee 45
3.2. DETAILS OF INDIVIDUAL TESTS 47
3.2.1 First 48-Hour Detailed Test ........... 0. cee reece eens 47
3.2.1.1 Test Date and Conditions ...............--. 47
3.2.1.2 Participating Vendors .........--+0-e eee eee 47

3.2.1.3 Problems and Exceptions to Test Procedures ... 48

ix



——

PHILIPS ELECTRONIC INSTRUMENTS COMPANY
INDUSTRIAL AUTOMATION DIVISION

2975 COURTYARDS DRIVE

NORCROSS, GEORGIA 30071, USA

THERMOCOAX NORCROSS NO: VB 901 D 003 |

PAGE: 1/5

DATE: 06/18/92

DISTRIBUTION: C

APPENDIX:
-E-BOND DATA SHEET
-CONCRESIVE PASTE

—

CUSTOMER REF:

|
|
|
|
|
|

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MANUFACTURING |

OMe AK id

REV DATE “AUTHOR DESIGN
QUALITY
oO 06/18/92 & T. LLOYD A. WHARTON aulal
-! nia - PL ¢,
\ atlas “fe Bo YY Pe pital

cr |

|

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F1001

This document is the property of Philips/Thermocoax, Norcross, GA and cannot

be reproduced without written authorization.



Sensor Heights (inches)

|

1

|
o 12 3 4 5 6 7
Distance from Solid Line (feet)

Figure 10. Mitron Axle Sensor Profiles

25

8

9



Table XV. Accuracy Summary for PAT AVC-100 (L-P-L)
ist 48-Hour Test

Correct
(ao 2,3) |

1
20-40 1.63 765 94.8 0.072 | 0.527 * . * .
40-60 1.05 85.0 96.9 0.014 |} 0.363
60-80 0.51 86.5 97.0 0.433 | 9.701
Air Temp
50-59 6.90 733 96.5 0.036 } 0.516
60-69 1.14 D6 95.6 0.106 | 4.530 * * . .
70-79 1.42 76.5 94.6 0.093 | 0348
80-89 1.82 76.4 94.5 0.107 | 0.564

Pav Temp
60- 69 13 75.4 95.8 0.077 | 5.346
10- 79 1.18 93 95.6 0.030 | 0.488
80- 89 1.49 769 95.2 0,079 | 0.386 * * * *
H- 99 1.46 76.2 94.2 0.102 | 0.381
100-109 1.48 16.7 95.4 0.119 | 0.393
110-119 2.06 76.2 93.9 0.100 | 0.666
Larrea

reniE G2 -_ vrs —
* ~ Overall Vehicle Length Not Calculated

mm = os oH

105



INSTALLATION COST
Varies with type of sensors

NOMINAL INSTALLATION TIME .
10 minutes with portable sensors; 1/2 day per lane with permanent sensors

INSTALLATION PROCEDURE
Tape or clamp for portable sensors; saw-cut and epoxy for permanent sensors

SOME STATES CURRENTLY USING THIS EQUIPMENT
Louisiana, New Mexico, Tennessee

OTHER COMMENTS .
Other equipment from IRD includes Weigh-in-Motion axle and vehicle
sensors, Automatic Vehicle Identification (AVI) toll plaza equipment

GTRI COMMENTS
Testing three configurations:

530-4B/BR/4L Bi’Piezo-Loop-Bi’Piezo
530-4D/4P/4L Dynax-Loop-Dynax
Piezo-Loop-Piezo
200



ee ee ee ee



ee ee

Table I.
Table H.

Table I.
Table IV.
Table V.
Table VI.
Table VII.
Table VII.
Table IX.
Table X.
Table XI.
Table XI.
Table XH.
Table XIV.
Table XV.
Table XVI.
Table XVII.
Table XVIII.
Table XIX.
Table XX.

Table XXI.

LIST OF TABLES

Vendor Classifiers and Configurations Installed ..............
Accuracy Summary for Mikros Systems TEL-2CM
ist 48-Hour Test

Accuracy Summary for Mikros Systems TEL-2CM ........... 73
2nd 48-Hour Test

Long-Term Count/Classification Accuracy ............-..4- 714
Mikros Systems TEL-2CM

Summary for Peek TrafiCOMP DI ............... 78

Ist 48-Hour Test

Accuracy Summary for Peek TrafiCOMP III ............... 82
2nd 48-Hour Test

Long-Term Count/Classification Accuracy ...........-. wees 83
Peek TrafiCOMP HI

Accuracy Summary for Peek GK-6000 (Lane 1) ............. 89
1st 48-Hour Test

Accuracy Summary for Peek GK-6000 (Lane 2) ............-. 90
1st 48-Hour Test ,

Accuracy Summary for Peek GK-6000 (Lane 1) ............. 96
2nd 48-Hour Test

Accuracy Summary for Peek GK-6000 (Lane 2) ............. 97
2nd 48-Hour Test

Long-Term Count/Classification Accuracy ............-..4- 98
Peek GK-6000 (Lane 1)

Long-Term Count/Classification Accuracy ...........--.045 99
Peek GK-6000 (Lane 1)

Long-Term Count/Classification Accuracy ................ 101
PAT AVC-100 (P-L-P) .

Accuracy Summary for PAT AVC-100 (L-P-L) ........-... 105
1st 48-Hour Test

Accuracy Summary for PAT AVC-100 (L-P-L) ............ 109
2nd 48-Hour Test

Long-Term Count/Classification Accuracy ...............- 110
PAT AVC-100 (L-P-L)

Binned Count/Classification Accuracy .......... 0.000 2c ee 112
Mitron MSC-3000 DCP - ist 48-Hour Test

Accuracy Summary for Peek ECM HESTIA .............. 116
Ist 48-Hour Test

Accuracy Summary for ECM HESTIA ..............+-0-- 120
2nd 48-Hour Test

Long-Term Count/Classification Accuracy ...............- 121

Electronic Control Measure HESTIA

xvii



The third test conducted was a 7-day test performed on September 9-16, 1993 in
conjunction with the second 48-hour test. During this test, the classifiers were programmed
to bin the data in 15 minute increments. The purpose of the test was to assess the long
term performance characteristics of the equipment. The data was compared to determine
how accurately the classifiers counted the number of axles, and the number of vehicles in
each vehicle class. The 7-day test was also used to assess the performance of the equipment
as a function of time in service by comparing the accuracy in the first day of testing with the
accuracy in the last day of testing.

An augmented pneumatic tube test was conducted in parallel with the second 48-hour
test. This test used a Peek TrafiCOMP III (Peek 241) and four road mbes to monitor the
traffic in two lanes. The objective of this test was to assess the ability of road tubes to
monitor traffic in multiple lanes. A setup error resulted in the classifier recording all traffic
in both lanes into one file. Therefore, the problem of separating the traffic into the two
lanes and removing duplications was made much more difficult. Therefore, analysis of this
test was postponed until a re-test can be conducted.

Ground truth data for the 48-hour and 7-day tests was obtained from a side-mounted
video camera viewing the traffic stream. The vehicle classes and measurements were
obtained from the video tape through the use of a computer-aided data reduction system
developed specifically for this project. The computer data reduction system was named the
Computer Vehicle Classification and Reduction System (CVCRS), and was capable of
assisting an operator in the recording of time stamped vehicle classes along with
measurements of axle spacings and overall vehicle length.

The classification accuracies resulting from this test ranged from 63.5% to 79.1%.
The most common errors occurred between Class 2 (passenger vehicles) and Class 3 (other
2-axle, 4-tire vehicles). A small pickup truck (class 3) is very difficult to distinguish from a
large car (class 2) based on length and axle spacing. If class 2 and 3 are combined, then the
classification accuracies ranged from 78.8% to 96.2%.

Temperature of the air and pavement was found to have little effect on the
performance of the classifiers. However, the range of temperatures was somewhat limited
for this test. The percentage of trucks (vehicles with more than 2 axles) tended to have
some effect on the classifier accuracies. The classification of class 9 vehicles (a majority of
the trucks) was very good on most classifiers, and hence the classification accuracy tended
to improve as the percentage of trucks increased. The longer vehicle lengths and axles
spacings did, however, result in greater measurement errors as the percentage of trucks
increased.

The sensor configuration used by the classifiers did not appear to have a significant
effect on the accuracy. Classification accuracy, axle spacing measurement errors, and overall
length measurement errors appeared to be independent on the sensor configurations. The
primary factor observed in this test to affect the classification accuracy was the performance

vi



5.2.7.2 Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 48. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 72.0% of the vehicles (94.3% if class 2-3
errors not included). The number of vehicle axles was miscounted 6.70% (percent sensor
errors) of the time. There were less than 0.7% of the vehicles classified by the HESTIA
that were the result of a suspected split or combination.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 49, The HESTIA classifier measures axles spacings, wheelbase length, and overall
vehicle length. The measurement error statistics (mean and deviation) for all
measurements, and the overall length percentile statistics are included in the figure as a
function of measured vehicle speed (mph). Note that all measurements are in feet.

Table XIX contains a summary of the results of the classification accuracy as a

function of percent vehicles with greater than two axles, air temperature and pavement
temperature.

117



me of lo See ee ee |

Axles Spacing Statistics

‘Speeds Mean

Wheelbase Statistics

Speeds Mean = STD Vehicles
<0 0.370 0.210 2
30.0-34.9 0.000 0.000 0
35.0-39.9 0.470 0.000 ?
40.0-44.9 °0.014 0.237 abd
45.0-49.9 0.079 0.256 51
$0.0-54.9 0.020 0.327 3146
55.0-59.9 0.015 0.390 1257
60.0-64.9 -0.018 0.360 3149
65.0-69.9 0.005 0.338 3757
70.0-74.9 0.028 0.265 1826
75.0-79.9 0.047 0.278 275
780 0.030 0.308 42
Overalt @.005 0.338 10689

Figure 41. Measurement Accuracy Versus Speed (MPH)
Pesk Gx-6000 (Lane 2) - 2nd 48-Hour T

95



Figure 22. The CVCRS System

As the data reduction proceeded continual modifications were made to the software
to improve its efficiency. For instance, a character recognition algorithm was added to the
software after the data reduction from the first 48-hour test. The character recognition
algorithm records time directly from the time displayed on the video screen saving the user
the effort to increment (or enter) the time. This saved the user approximately 20-25% of
the time required to enter each vehicle. Also, the five days of the second test not used for
detailed vehicle-by-vehicle comparison did not need measurement of vehicle lengths and
axle spacings. Therefore, a second version of the program (“CVCRS2.c") was made which
simply recorded the time from the video, and saved the vehicle class and number of axles
entered by the user. The second version of the software allowed the user to record vehicle

data at nearly twice the rate of the original software.

The typical steps required to operate the CVCRS for detailed vehicle-by-vehicle data
treduction are as follows:



DIAMOND TRAFFIC PRODUCTS
P.O. Box 975
Port Richey, FL 34673-0975

SALES REPRESENTATIVE
Jerry Schiff (813) 843-0270
FAX (813) 843-0270

MODEL NAME
Traffic Tally 2001

GENERAL DESCRIPTION OF EQUIPMENT
Multi-lane vehicle classifier. Operates in raw data or binning mode, up to four
lanes classification or eight lanes of count. Available with inductive loops,
piezoelectric sensors, or road tubes. Equipment also operates with remote
center line air switch.

METHOD OF OPERATION
Unattended, capability to access data via telemetry is standard.

METHOD OF DATA STORAGE
Battery-backed static RAM.

DATA STORAGE CAPACITY
68K Standard. Memory can be expanded up to 960K in 128K increments to
allow collection of more raw vehicle data.

VEHICLE CLASSIFICATION SCHEME
Raw data and up to 20 bins, but FHWA Scheme F is default setting.

POWER SOURCE
12 Volt 6-1/2 amp-br Lead Gel/Solar/110 Volt rechargeable internal battery
(new equipment uses 6V 12 amp-hr batteries)

OPERATING TEMPERATURE RANGE
.-40°F to 158°F (Electronics)

OPERATING VEHICLE SPEED RANGE
5 to 105 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
12" x 12" x 7.5", 1/8" T-5052 welded alum. construction - 18 Ibs

MAXIMUM LENGTH OF LEAD CABLE
Loops - 800 feet; Piezo - 800 feet +

PURCHASE COST OF EQUIPMENT
$1450 to $3100

193



is

om ie me mo we ee ee eo oe et mm

10.

Using a straight edge (10 foot aluminum bar in this case), lay out the
sensor configuration and paint guide lines on the pavement. Ensure
visually or by measurement that the sensors are perpendicular to the road.

Cut each outside edge of the slot with the saw adjusted to the vendor
specified depth. Make three or four more cuts inside the previous cuts
leaving thin sections of pavement to be removed. Cut a 1/4 slot to the
edge of the pavement for the coax cable. To protect the coax from future
damage, make the cut deeper near the edge so that the coax will exit the
pavement well under ground level.

Chip out the excess materia] using a pneumatic chisel or a hammer and
chisel. Use a plywood jig or a ruler to check the depth of the slot. Test fit
the sensor to be sure of a proper fit.

Wash the slot thoroughly, and blow out any debris using compressed air.

Blow out the slot for a few minutes with compressed air to remove any
remaining water. Allow the slot to dry thoroughly. Propane torches or
torpedo heaters (forced-air, kerosine heaters typically 100,000 BTU) may
be necessary depending on conditions. If propane torches are used, do not
overheat or melt the asphalt. Torpedo heaters can be utilized more
effectively if the hot air is channeled over the slots through tunnels made
of cardboard or aluminum sign blanks. In cold conditions, torpedo heaters
can also assist in curing of the epoxy by preheating the slot.

After the slots are dry, brush all sides with a wire brush to dislodge any
dust or dirt that may reduce epoxy adhesion. Blow the slots out a final
time with compressed air.

Prepare the sensors by attaching leveling bars (typically steel bar stock) to
hold it at the right height relative to the pavement surface. The bars are

attached using wire or plastic tie-wraps.

Form a dam at the coax end of the slot using plumber’s putty to prevent
the epoxy from flowing out of the sensor slot. Place duct tape along the
top of the slot on each side to prevent excess epoxy from adhering to the
pavement. Multiple layers of tape can be used to raise the sensor slightly
above the road surface by holding the leveling plates slightly higher.

Mix the epoxy following the manufacturer’s directions. Use a pneumatic or
a heavy duty electric drill with a mixing paddle attached. Large paddles of
the type used for drywall sealer work very well.



Axles Spacing Statistics

Speeds

<0
30.0-34.9
35.0-39.9
40.0-44.9
45.0-49.9
50.0-56.9
35.0-5
60.0-64.'
65.0-69.9
70.0-76.9
‘%5.0-79.9

>80

Overall

0.018

sTD

wheelbase Statistics

&
é

passusasyg
pat ig a aad a

8

H

Figure 53. Measurement Accuracy Versus Speed (PE)

Mean

0.000
0.000
0,000
0.207
0.071
0.058
0.027
70.040
0.062
-0.059
0.074
0.051

+0.060

o o

o 0

0 0

3 3
% 2B
1% 323
75 1870

Tr = 1027
9 100
uw »

stp Vehicles

6.000 0
0.000 oO
9.000 o
0.918 3
0.450 4
0.497 134
0.616 715
0.477 2673
0.454 1946
0.349 rca)
0.343 90
0.316 &
0.4674 6380

TimeMark Delta II -

128

2nd 48-Hour Test



APPENDIX D
MATERIALSPECIFICATION/INSTRUCTION SHEETS
225



LIST OF FIGURES

Test Instrumentation Conceptual Drawing

Overali Layout of Evaluation Site .........
Mikros Installation Configuration Drawing -
Mikros Axle Sensor Profile ......-..:..--
Peek Installation Configuration Drawing
Peek Axle Sensor Profiles .......-..---+--0-
PAT Installation Configuration Drawing
PAT Axle Sensor Profiles .......-..----000>
Mitron Installation Configuration Drawing
Mitron Axle Sensor Profiles .........--.---+-
ECM Installation Configuration Drawing .
ECM Axle Sensor Profiles ..........--
TimeMark Installation Configuration Drawing
TimeMark Axle Sensor Profiles ...........---
IRD Installation Configuration Drawing ........
IRD Axle Sensor Profiles ..........-
GRI Installation Configuration Drawing .
GRI Axle Sensor Profiles ............+-5
Diamond Installation Configuration Drawing .
Diamond Axle Sensor Profiles

Correct Configuration of the Lane-Change Camera, Time/Date ..... 50
Generator and VCR

The CVCRS System ........ cece cee eee eee tet eee nee 54

The Standard Data Format ........... cece eet ee eee eee e eee 58

Example Output of the BINNED Program .......-..-...---2 ees 62

Example Output of the Analyze Program ...........-0---20-00005- 63

Classification Matrix for the Mikros Systems TEL-2CM ..........-. 67
ist 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .........-------++5 68
Mikros TEL-2CM - ist 48-Hour Test

Classification Matrix for the Mikros Systems TEL-2CM ...........- 71
2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ..........----00-5- 72
Mikros TEL-2CM - 2nd 48-Hour Test

Classification Matrix for Peek TrafiCOMP HII ...........---.---- 16
1st 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........----.0-00+ 71
Peek TrafiCOMP HI - ist 48-Hour Test

Classification Matrix for Peek TrafiCOMP IT .........-..--2-+5- 80
2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .......-..----+00+- 81

Peek TrafiCOMP Hl - 2nd 48-Hour Test



5.2.82 - Second 48-Hour Test

The classification matrix for the second 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figure 52. The classification matrix is presented in both absolute numbers, and
percentages. The classifier correctly classified 77.3% of the vehicles (94.6% if class 2-3
errors not included). The number of vehicle axles was miscounted 1.97% (percent sensor
errors) of the time. Approximately 1.3% of the vehicles classified by the Delta II were the

Tesult of a suspected split or combination.

There were more than 11,600 vehicles missed (see "#Missing Vend:" in Figure 54)
by this classifier that were recorded on video tape. Most of the other vendors missed less
than 2000, most of which can be accounted for by lane changes. By reviewing binned data
for this classifier and the ground truth data, it was found that roughly half of the class 2 and
3 vehicles were missed by this classifier. Apparently, the sensitivity of the sensors and
classifier electronics was not sufficient to detect a large number of the passenger cars and
small trucks. While the classification accuracy of those detected was fairly good, a large
number of vehicles were missed by this unit.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figure 53. The TimeMark classifier measures axles spacings and wheelbase length. The
measurement error statistics (mean and deviation) for all measurements are included in the
figure as a function of measured vehicle speed (mph). Note that all measurements are in

feet.

Table XXII contains a summary of the results of the classification accuracy as a
function of percent vehicles with greater than two axles, air temperature and pavement

temperature.

126



Axies Spacing Statistics

Speeds Mean $1D Veh aAxle_Spacings
0.000 ° 9
0.000 oO oO
9.000 1 1
0.000 9 9
0,000 1 1
9.421 235 38
0.737 150 325
0.378 415
0.430 587 1054
0.605 268 378
0.447 67 ?
0.904 3 3B
0.498 1537 2817

Speeds Mean = STDs Vehicles:

Overall 0.373 0.661 1537

Length Statistics

0.000
0,000
2.720
0.000
-3.350
-2.820
72.443
72.626
+2.376
+2.030
“1.972
2.752

72.382

s1D

Vehicles

1537

Length Percentile Statistics

Speeds wean STD
<0 0.00 0.00
30.0-34.9 0.000 0.000
35.0-39.9 122.295 0.000
40.0-44.9 0.000 0,000
45.0-49.9 82.275 0.000
50.0-54.9 91.556 5.835
55.0-59.9 91.553 5.994
60.0-64.9 91.165 5.755
65.0-69.9 90.733 5.467
7O.0-74.9 FO.G47 6.734
75.0-79.9 89.413 7.387
BD 88.45 22.17
Overall 90.82 6.56

Figure 71. Measurement Accuracy Versus Speed (MPH)
Diamond TT-2001 (Philips) - 2nd 48-Hour Test

169

Vehicles



MIKROS SYSTEMS

je 5-30"
en
PI |
W 1 12 s
54 <I - Xe
at a WO bse |
md T 200"
woo" | y) i
| ~~ 4
v

|
!
|
|
|
|
|

LL
L_]
EQUIPMENT
CABINET

Figure 3.

Note; Both foops
are 8 X J-3.0"

Mikros Installation Configuration Drawing

14

ee ee oe |

iw mm 2 we mr a me oe



Axles Spacing Statistics

Speeds Mean STD Veh axie_spacings
<30 + 558.115 591.180 6 8
30,0-34.9 2.098 13.125 6 18
35.0-39.9 -26.070 98.663 ) 7
40.0-66.9 70.280 28 100
45.0-49.9 10.963 102,324
50.0-56.9 38.716 313625,
55.0-59.9 16.3% | 1146 1875
60.0-64.9 16.509 | 3261 5182
65.0-69.9 16.172 40756169
70.0-76.9 24.635 20992636
%5.0-79.9 11.552 4450523
280 261.423 1272
Overatt 45.606 11607 17764

Wheelbase Statistics

Speeds Mean = S1D_—s‘ Vehicles
BO -1674,345 1739.790 6
30.0-34.9 6.295 11.000 6

-100.165 260.605 9
-56.598 180.700 28
723.280 16.209 102
712,856 75.988 313

“4.587 13.629 1146
4.599 13.778 3261
73.775 14.416 4075
~2.601 34.359 2099
71.502 9.046 445,
=162.144 592.644 127

Overall -7,.078 88.453 11607

Figure 63. Measurement Accuracy Versus Speed (MPH)
Golden River Marksman 660 - 2nd 48-Hour Test

151



meee eee eee

5.2.13.3 Seven-Day Test

The résults of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XXXVIII. The totals for
the entire seven days for the vendor and classifier are listed. Also, the difference (ground
truth minus vendor) and the percent difference (ground truth * 100 / classifier) are listed.
To assess the change inaccuracy over the seven days, the percent difference is calculated for
the first and last of the seven days.

Table XXXVIII. Long-Term Count/Classification Accuracy
Diamond Traffic TT-2001 (Philips)

| Total * Total
Grod Truth | Classifier

| Class 15 | 0 6113 6113 0.00 0.00 -

qi



Once the sensor is set to the proper height, place
it alongside the channel. Place some tape around
the cut slots - see Figure 11 - to keep excess
epoxy off the road surface. The tape should be
around the entire perimeter of the cut slot. Insert
the Jead wire into the cable slot, and build a
small dam around it using clay or an equivalent, wn a wae mn
so that the epoxy does not leak past the sensor

HEAVY DUTY DUCT POLYETHYLENE TAPE,

Page 5

AREA woncny NEEDS 10 OL RAISED:

Road mmr AcT

PUSH Dow GENTLY AT ARROWS, USE NO MICHER THAN 7° BLOcK!

slot into the

cable slot. Figure 10: VERY CAREFULLY bend the sensor
to conform to the road

Mix the

epoxy/grout according to manufacturer’s instructions (See
appendix 1, epoxy notes). Using a plastic bucket or trowel
(depending on consistency of epoxy), carefully pour the
epoxy/grout into the cut slot until the channel is a little less
than 2/3 full. (Figure 12) Be as neat as possible. Once the

Se

epoxy is poured into the slot,

gs oa
ee 2 the sensor should be placed
Moe Ce P

LPO a

into the slot as before - see

Figure 11: Heavy polyethylene Figure 9. Once the sensor is

tape is used 10 keep the epoxy off Hut into the channel, pull any

¢ road .

extra lead wire to remove the

slack being sure the dam

remains in place. Be sure the sensor is properly seated. Any

voids should be filled. Carefully removed any excessive

amounts of epoxy from the installation. There must be a
smooth transition between the sensor and the road surface.

Weights (bricks do well) may be placed on top of the
brackets/sensor but it is recommended to put a layer of
polyethylene over the sensor to avoid sticking. Allow the epoxy
to cure as per manufacturer’s instructions. A ‘heat tunnel’ can
be constructed from cardboard boxes or the sensor shipping box

Figure 12: The slot is filled 2/3
full with epoxy

if curing time is critical (Figure 13), but, be careful not to get the heat source too close to the

cardboard; it may burn!

Route the lead wires to the electronics, keeping the length of the lead wire and the number of
tums should be keep to a minimum. If unable to hook up to the electronics immediately, be
sure that the exposed end of the lead wire is protected from water penetration and the cable is
protected from damage. Conduit is recommended for wire routing but plenum cable may be
buried in the ground without conduit. Use caution while burying the cable with conduit being
careful not to damage the cable with tools or sharp objects in the ground.

Once the epoxy has gelled to a semi-hard state, cut the cable ties and remove brackets if these
have been used. Trim off any exposed part of the cable tie and remove the tape from around

Elf Atochem Sensors inc, PO Box 799, Valley Forge, PA 19482 ® (215) 666-3500 Fax (215) 666-3509



Page 2

>| out 3 feet along the line or road edge and place
| a mark, called position "B’. Keeping the same
pivot point (position *A'), rotate the tape straight
out onto the roadway, placing the crayon at the 4
foot mark, and marking an arc about 1 foot long.
Now move the end or pivot point of the tape
measure to position "B’ (on the road edge) and,
repeating the above procedure, measure out 5
feet and draw another 1 foot arc so that it
intersects with the arc already drawn. Where
these two arcs intersect is position °C’. Using a
straight edge or chalk line mark a line on the roadway using positions "A’ and ’C’ as guidelines.
The line should be a little longer than the sensor shipping box, or about 7 feet. This line will
be perpendicular to the traffic flow.

STS:
Ss

SS

SPRAY Panel (seRAY 0 OUTUME ALL {DOES}
#C BURE TO SOMAT TRS ARTA 100

Figure 2: Use tape and 2 waterproof traffic paint
to define the ares to be cut.

Now mark the cutting location. Measure the sensor (end of sensor to beginning of lead
attachment area), then add a couple inches to this. This measurement will be Jength L on Figure
2. Decide where the sensor should be placed (typically the end of the sensor at the lead attach
end will originate from the edge of the edge stripe closest to the shoulder. Place the masking
tape as shown in Figure 2, a nd using waterproof, quick drying traffic paint, spray over the tape.
When the paint is dry, remove the tape exposing a
pattern on the roadway which will be used as a cutting
guide, as shown in Figure 3.

SENSOR SLOT GUIDE
Carefully move the sensor completely out of the work
area. Be careful with the sensor so as not to damage it.
Although the passive signal cable has a tough outer
jacket, it should be handled carefully. Be especially
careful not to step on it or nick it - the Jacket can
crack if it is nicked and then sharply bent at the nick
point. Also remove any other equipment which could be
damaged by dust and grit, since the cutting process

generates a significant amount of debris CABLE SLOT GUIDE

. . ROAD SURFACE
A diamond tipped blade is recommended for slot cutting,

although abrasive blades may be used by experienced
personnel. The blade width ideally should be between
1/4" - 1/2" wide, but thinner blades may be used. If
using abrasive blades which are 1/8" wide, ‘bank’ two
blades together to give the 1/4" recommended width. Wet cutting blades are generally preferred
by most contractors, though dry cutting blades are available and may be preferabl: during cold
weather or when water supplies are not available. Always use dust masks when dry cutting!

Figure 3: Cut the slot in the sensor slot
guide area.

Using the guide marks on the road (Figure 3) begin the cutting. Cut the sensor slot first, cutting
out the un-painted area (Figure 4) and leaving the painted marks. Two passes should be made,

Elf Atochem Sensors Inc, PO Box 799, Valley Forge, PA 19482 @ (215) 666-3500 Fax (215) 666-3509

holding a tape measure at position °A’, measure -



[—ne we eS

5.2.23 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table VII. The totals for the
entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the
first and last of the seven days.

Table VII. Long-Term Count/Classification Accuracy
Peek TrafiCcomp III

Axles 165917 N/A N/A N/A N/A N/A
| Classi] 103 604 -501 17.05 16.05 15.19
jos 2 31124 41126 -10002 7568 76.58 75.40

Class 3 19417 6377 13040 304.48 292.89 267.08

Class 4 138 283 “145 48.76 31.82 37.21

Class § 1921 1157 164 166.03 99.43 116.77

Class 6 746 736 10 101.36 100.00 101.64

Class 7 9 4 5 725.00 ~ -

Class 8 1 862 2204 -1342 30.11 47.44 43.95

Class 9 9981 8427 1554 118.44 117.17 118.31

Class 10 109 86 2B 126.74 136.36 141.67

Class 11 254 248 6 102.42 100.00 102.27

Class12_ || 70 iw 7 90.91 100.00 100.00

0 ;
0 :



Table XXII. Accuracy Summary for TimeMark Delta TI
Ast 48-Hour Test

Sensor } Correct | Correct
Errors (no 2,3)
94.4

Axle | Axle | Length | Length
Mean { SD. | Mean SD.
0.124 | 2,791 * *

2.83 78.9
2.77 163
291 BS
3.41 863

943
945
92.2
963

0.496
0.646 . . .
0.363
12.44

90.5
939

| Pav Temp

60- 69 1,16
70-79 3.50
80- 89 3.96
90- 99 2.50
100-109 2.65
2.56

beers

90.7
81.6
BA
782
714

0.553
0.076
0.075
6.677
0.101

B9 95.1 0.088
TT Does Not Calculate Ove!

9.668
0.634
0.501 .
0.445
0.642

0.761
sn a rom

125



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Combinations:

76



PAT EQUIPMENT CORPORATION, INC.
1665 Orchard Drive
Chambersburg, PA 17201-9206

SALES REPRESENTATIVE
Siegfried Gassner (717) 263-7655

FAX (717) 263-7845

MODEL NAME
AVC 100 Vehicle Classifier

GENERAL DESCRIPTION OF EQUIPMENT
Multi-lane vehicle classifier. Operates in binning mode, up to four lanes
classification or raw vehicle data collection. Available with inductive loops,
piezoelectric sensors, or road tubes. Uses a loop-axle detector-loop or axle
detector-loop-axle detector configuration.

METHOD OF OPERATION
Unattended, capability to access data via telemetry is standard.

METHOD OF DATA STORAGE
Battery-backed CMOS RAM.

DATA STORAGE CAPACITY
256K Standard. Memory can be expanded up to 4M.

VEHICLE CLASSIFICATION SCHEME
FHWA Scheme F is default setting and other types can be added up to a total
of 48 bins

POWER SOURCE
12V, 30 VA solar power panel
12V, 6 VA line - DC supply
(internal battery for backup of parameter, clock, and data memory)

OPERATING TEMPERATURE RANGE
-50°F to 175°F (Electronics)

OPERATING VEHICLE SPEED RANGE
> 2 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
16" x 15" x 8.5" steel housing - 15 Ibs .

MAXIMUM LENGTH OF LEAD CABLE
The axle sensors are supplied with a 65’ standard length cable. This cable can
be extended up to an additional 300’ by using a splice kit and coax cable.
Should several sensors be installed at a road section, the cables can be
concentrated in a bundled multi-conductor coax cable with a maximum length

205



hydroplaning of vehicle tires or interference with the magnetic loops, the degradation is
expected to be relatively minor. However, there is no test information which can be used
to validate this assumption.

Question 9. How accurately can-devices- monitor overall vebicle-lengi as a function of id 1 traffic vol icle mix?

The accuracy of the classification devices which measured overall vehicle lengths is
listed in Tables XLI and XLII. In Table XLI, the mean and standard deviation of the
measurement errors (ground truth (true) length minus measured length) are listed for each
vendor, classifier mode! and test. In Table XLII, the mean and standard deviation of the
percentage length measurements are listed. The length percentage is calculated by
multiplying the true length by 100 and dividing by the length measured by the classification
equipment. These tables are summaries of the results of the individual classifiers listed in
Section 5.2.

The effects of traffic speed on the overall length measurements of the individual
classifiers can be examined by reviewing the figures in Section 52. The effects of traffic
speed on the accuracy of the overall length measurements varied considerable from classifier
to classifier. The Electronic Control Measure HESTIA had increasing mean errors at
higher speeds (approaching 70 mph). The Mikros TEL-2CM showed a trend towards higher
errors at lower speeds. The International Road Dynamics TC/C 530-4D/4P/4L and the
Diamond TT-2001 units tended to have the greatest accuracies at speeds near 50-55 mph,
and tended towards higher errors at higher and lower speeds (though there were very few
vehicles with much lower speeds).

The accuracy of overall length measurements as a function of the air and pavement
temperature tended to be nearly constant. The accuracy varied very little as the
temperature changed for the classifiers tested. This is reasonable since the overall length
measurements are made primarily using the loop sensor inputs (and possibly speed
measured by the axle sensors). Magnetic loop sensors do not exhibit large variations as a
function of temperature.

The overall length measurement accuracy as a function of the percentage of trucks
(vehicles with greater than two axles) tended to degrade as the percentage of trucks
increased. The magnitude of the mean error in overall length measurement increased by
as much as 40% when the percentage of trucks increased from 0-20% to 40-60% (HESTIA
during Test 2). .

The accuracy of overall length measurements as a function of the traffic density is
nearly impossible to separate from the accuracy versus temperature and percent of vehicles
with greater than two axles. The high volume traffic occurred during the daytime hours
where temperature was highest and the percentage of trucks was lowest. The traffic at the

178



Figure 34.
Figure 35.
Figure 36.

Figure 37.

Figure 38.

Figure 39.

Figure 40.
Figure 41.
Figure 42.
Figure 43.
Figure 44.
Figure 45.
Figure 46.
Figure 47.
Figure 48.
Figure 49.
Figure 50.
Figure 51.
Figure 52.
Figure 53.
Figure 54.

LIST OF FIGURES (cont.)

Classification Matrix for Peek GK-6000 (Lane 1) ..........-+--00>

1st 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ..........2--00020-

Peek GK-6000 (Lane 1) - 1st 48-Hour Test

Classification Matrix for Peek GK-6000 (Lane 2) .....------------

1st 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ....-.----0--seeees

Peek GK-6000 (Lane 2) - Ist 48-Hour Test

Classification Matrix for Peek GK-6000 (Lane 1) ......-..--+---5-

2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .......--.---2e eee

Peek GK-6000 (Lane 1) - 2nd 48-Hour Test

Classification Matrix for Peek GK-6000 (Lane 2) .........-- 02s eee

2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........-----20-+=

Peek GK-6000 (Lane 2) - 2nd 48-Hour Test

Classification Matrix for PAT AVC-100 (L-P-L) ........ Sesevecee

1st 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .......--.------+-

PAT AVC-100 (L-P-L) - 1st 48-Hour Test

Classification Matrix for PAT AVC-100 (L-P-L) ........------05+

2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........-------0+>

PAT AVC-100 (L-P-L) - 2nd 48-Hour Test

Classification Matrix for ECM HESTIA ............---0ee esas

1st 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........-.----0-5-

ECM HESTIA - Ist 48-Hour Test

Classification Matrix for ECM HESTIA .............2- sees eens

2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) .......-----+.005>

ECM HESTIA - 2nd 48-Hour Test

Classification Matrix for TimeMark Delta T ............--+-+-+

ist 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ...........-----5+

TimeMark Delta II - 1st 48-Hour Test

Classification Matrix for TimeMark Delta TT ............22--055

2nd 48-Hour Test

Measurement Accuracy Versus Speed (MPH) ........-.--+---+5

TimeMark Delta II - 2nd 48-Hour Test
Classification Matrix for IRD TC/C 530-4D/4P/4L
(PR-L-PR) 1st 48-Hour Test

xiv



Table VI. Accuracy Summary for Peek TraficomMP IIL
2nd 48-Hour Test

0-20 2.96 BS 93.7 0.069
20-40 3.74 75.6 93.1 0.061 | 0.361
0.069

0.059
70-79 3.29 755 93.8 0.045 | 0331
159 0.107

683 0.061 | 0.385

70-79 3.95 48 92.0 0.062 | 0.347
80- 89 3.23 76.4 94.1 0.036 | 0.334 * * * .
90- 99 3.44 TAs 93.9 0.049 | 0346
100-109 2.43 71 95.0 0.088 | 0.365

i 2.91 48 932 0.069 | 0.363
= ——

FT Poes Not Measure Overall Venice Tength "



5.3. CLASSIFICATION ACCURACYVERSUS SENSOR ERRORS

The classification accuracy of all the equipment tested appears to be dependent on
the sensor accuracy. A sensor error, as listed in Section 5.2, is defined for this analysis as

nz miscount of the pumber of axles of avehicle. The number of sensor err:
a miscount of the number of axles of a vehicle. The number of sensor error were calculated

for each of the classifier equipments and each of the 48-hour tests. A plot of the

classification accuracy (percent correctly classified) versus the percent of the vehicles which
had sensor errors for both test 1 and test 2 is depicted in Figure 72. The lower points on

the plot are the total percent correctly classified, and upper points are the classification
accuracy ignoring errors between class 2 and class 3 (the most common classification error).
The classification errors appear to be linearly dependent on the sensor error (axle
miscounts). By extrapolating the data, it appears that the classification accuracy would
average about 78% if there were no sensor errors and 96% if errors between class 2 and 3

were ignored.

Note that data recorded by the Diamond Traffic TT-2001 classifier during the second
48-hour test was not included in the plot. The Diamond classifier had a software bug which
resulted in the recording of excessive errors which would bias the results in the plot. Data
from the Mitron MSC-3000 DCP classifier is not included since the Mitron classifier did not
generate vehicle-by-vehicle data.

100
° [ = Test 1
toe @ Test 1 (no 2-3)
8 Lar oe ° 5 Test 2
; oe & Test 2 (no 2-3)
90 +—_~+
3 ‘ ° 4
% 8s
3 a a
is) r
= 80 wo s ° |
— pn a .
& 75 = =
= . a a.
70 as *
s
65 — a
ob q
60
0 2 4 6 8 10 2 14
% Sensor Errors

Pigure 72. Classification Accuracy Versus Sensor Errors

172



Time interval: 2

Wo 2 GB % 15

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87

Figure 36.

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PEEK TRAFFIC, INC.
1500 North Washington Bivd.
Sarasota, FL 34236

SALES REPRESENTATIVE
Jim Stemitz (813) 366-8770

FAX (813) 365-0837

MODEL NAME
GK 6000 Series Counter/Classifier

GENERAL DESCRIPTION OF EQUIPMENT
Two or four-lane vehicle classifier. Operates in binning mode. Can operate
with loops, piezoelectric cable, or road tubes.

METHOD OF OPERATION
Unattended.

METHOD OF DATA STORAGE
Battery-backed RAM. Can be expanded with the optional Data Module.

DATA STORAGE CAPACITY

ANG AADAL aith SAL antions’
40K (104K Will 64K Optidna:

9

VEHICLE CLASSIFICATION SCHEME
Up to 14 bins

POWER SOURCE
Rechargeable 6 Volt 16 amp-hr sealed lead acid gel battery

OPERATING TEMPERATURE RANGE

-40°F to 158°F (Electronics)

OPERATING VEHICLE SPEED RANGE
5 to 128 mph

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
8.25" x 8.5" x 5.75" - 6.31 Ibs

MAXIMUM LENGTH OF LEAD CABLE
Up to 1000 feet. (varies with set up)

PURCHASE COST OF EQUIPMENT
$1,500 to $4,000

INSTALLATION COST
Varies with users desire for type of sensors.



APPENDIX A
PARTICIPATING VENDORS AND CONTACT PERSONS
187


Question 6, Se een En a aE EST iby f vehicles wit axl ! ef
stream being measured?

The equipment accuracy as a function of the number of trucks (vehicles with greater
than two axles) for each classifier is presented in tables in Section 5.2. In that section, it
shows that the classification accuracy as a function of the percentage of trucks does tend to
show an improvement as the percentage of trucks increases. However, the percentage of
trucks generally rose dramatically in the late evening and early morning hours when the
traffic volume was very low. The effects of the lower traffic volume is likely to have had at
least as great an impact on the classification accuracy as the percentage of trucks in the
vehicle stream.

The general patterns of incorrect classifications showed no appreciable change as a
function of the number of trucks in the traffic stream. The total number of class 3 vehicles
classified as class 2 (the most common classification error) decreased as the traffic volume
and number of class 3 vehicles decreased, but the tendencies and percentage of class 3
vehicles incorrectly classified stayed nearly the same.

Axle spacing measurements tended to show little or no appreciable variation with the
percentage of vehicles with more than two axles. The response of individual classifiers are
shown in tables in Section 5.2.

Question 2, What is the i f i/or_ai .
accuracy?

The impact of pavement and air temperature on the classification and axle spacing
measurement accuracy for each classifier and test is presented in tables in Section 5.2. Very
few conclusions can be drawn from the data collected from the tests conducted in this
project. The range of temperatures experienced during the test was relatively limited with
no near or below freezing air temperatures experienced. Over the range of air and
pavement temperatures experienced during the two 48-hour tests, the classification accuracy
appeared to vary very little. At very low pavement temperatures (60-69 degrees), the mean.
error did appear to rise slightly, but at these times (early mornings) the traffic was also very
light and consisted mainly of large trucks. Therefore, the measurement of axle spacings
appeared to be affected very little by the temperature ranges experienced in these tests.

ion & What is the i f precipitati .

During the tests performed for this project, no apprecjable precipitation was
recorded. Therefore, no information of sensor or classifier accuracy can be derived from
the test results. All of the classifiers tested used combinations. of piezoelectric sensors and
magnetic loop detectors. While there is the possibility of some sensor degradation due to

177



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Pigure 42.



2tQ©
LANE CHANGE CAMERA a
MONITOR
oe
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TIME/DATE GENERATOR VIDEO CASSETTE RECORDER

Pigure 21. Correct Configuration of the Lane-Change Camera,
Time/Date Generator and VCR

have the capability to imprint time and date on the video. A time/date generator was
added in the line between the camera and the VCR to add the time and date to the video
image before being recorded. This configuration is shown in Figure 21. During the second
test, the VCR and time/date generator were accidently swapped in the configuration. Thus
the time and date was displayed on the local monitor during the test, but was not recorded
by the VCR for use during data reduction. Careful use of the VCR’s tape time counter and
manual time synchronization with the pole camera was required to match vehicles that
change lanes with the appropriate vehicles in the ground truth data. This problem did not
affect the results of the test.

The road tube test appeared during testing to be working properly. During data
reduction, however, it was found that the classifier had been set up to sum the traffic in both
lanes and not record the traffic counts in individual lanes. This would have made it very
difficult to separate the traffic to determine errors in the count due to 2 or more vehicle in
different lanes passing over the sensors at the same time. The data is still being reviewed,
but the initial assessment indicates that the test will need to be repeated in order to obtain
accurate data. Currently, the plans are to repeat the test in parallel with a follow-on test.
The results will likely be available for the final version of this report.

The problems experienced with the participating vendor’s equipment during the
second 48-hour test are as follows:

e Peek GK-6000 - This classifier required periodic downloads to a PC to store
data. During these downloads, the classifier didn’t record traffic data. The

50



Site Selection

The selection of the site is a critical factor for both the life of the sensor and the

accuracy of the measurement. The sensor installed in the pavement is surviving fot
only the traffic but also of the road deformations and movements.

* — It is obvious that sensors must not be installed in pavement that is uneven, deeply
rutted, cracked. They must be installed in a homogeneous material (concrete or
asphalt) and not in 2 adjacent layers.

The signal delivered by the Vibracoax sensors is proportional to the dynamic weight of
the vehicle axles. To get a signa! as close as possible to the static weigh, all vehicie
vertical acceleration must be prohibited. This means: -
- the pavement must be reasonably fiat for 100 yards ahead of the sensor,
- avoid curves, inclines or declines,

- avoid crossings, traffic lights, railroads...,

- avoid areas of speeds less than 20mph.

1V. — Sensor Installations .
The installation process is to remove part of the pavement to install the sensor in it
and to secure it via a grout. Best results are achieved when the sensor is flush to the
top surface of the pavement. To allow a fast reopening of the highway lane, the
pavement and the grout are usually heated between 90° to 100°F. The sensors are
designed to easily survive this temperature ht care must be taken to avoid
overheating of the grout which can damage the extension cable. While curing the
grout, temperature will rise by another 20° to 30°F depending on the size of the
groove (the larger the groove, the larger the rise}. A careful control of the grout
temperature is a must.

The 50 ohms extension cable can also be damaged by bad handling. Avoid: twists,
kinks, knots....

For a proper installation foliow these steps:

- Step 1: Protection of the site with the required signs and cones for safe
operation.

- Step 2: Mark the pavement with paint for loops and sensors. The slot size for
Vibracoax sensors is 2” wide, 2" deep and 3" longer than the sensor.
For Class 2 sensors, as they are only 6 ft long, be sure that they are
aiways hit by one wheei per axie. Ciass 1 sensors must be hit by both
wheels.

AUTHOR: GB PAGE: 3/5
CODE: VB 901 D 003 REV: O

THERMOCOAX NORCROSS



b. Enter all of the points described in step 5 that are displayed on the screen,
but DO NOT exit the data entry screen.

c. Choose a distinct vehicle feature (mark, reflector, axle, etc.) behind the
middle of the vehicle, align the vertical bar of the crosshair with the selected

feature, and hit "r" on the keyboard.

d. Advance the VCR tape and pause it such that the rear of the vehicle and the
feature chosen in step 7c are both on the screen.

e. Align the vertical bar of the crosshair with the feature selected in step 7c and
again hit "rc" on the keyboard,

f. Finish entering axles and the rear of the vehicle as described in step 5.
Upon returning to the main menu, the user verifies the vehicle classification guess
made by the program and the time recorded from the video. Either of these items

can be changed by clicking on the appropriate selection in the middle of the main
screen. :

The data is saved using the “Save Data” option at the top of the main menu.

The steps required to operate the CVCRS2 program for less detailed data analysis

are similar, but less complicated than those required to run the CVCRS program. Steps 1
through 3 and 9 are identical, but steps 4 through 8 are replaced by:

4.
5.
6.

7.
8.

4.2

Advance the tape until the vehicle is centered on the screen.
Enter the vehicle class and number of axles using the keyboard.

Select "Re-enter Vehicle" on the main menu if an error is made, and repeat steps 4
and 5.

Verify time recorded by the program and edit if necessary.
Hit <Enter> or <Return> on the keyboard to start next vehicle.

HANDLING LANE CHANGES

The use of the long (600 foot) test site meant that a significant number of vehicles

changed lanes within the site. A vehicle changing lanes will only be recorded by classifiers
over which it passed, and can cause errors in those classifiers which it passed over while
changing lanes. Also, if the vehicle entered the test lane after passing the pole camera, it
would not appear in the ground truth data. Therefore, all vehicles that changed lanes within

56



186



1. INTRODUCTION AND SCOPE
1.1. Background

There have been significant changes in the sophistication and technological
approaches to the gathering of vehicle classification and volume count data since the last
major study of vehicle classification accuracy. This has included the use of new types of
sensors, such as piezoelectric, the development of programmable classifiers that allow the
user to specify the dimensional thresholds for various vehicle types, and the introduction of
vehicle classifiers that retain individual vehicle information rather than binning the data.
This study addresses the need for controlled testing of the latest Automatic Vehicle
Classification (AVC) equipment. The equipment is limited to commercially available
devices that provide volume counts and vehicle classifications.

The objectives of the program are to:

Determine the adequacy of vehicle counting devices.

Determine the adequacy of various types of equipment ‘to correctly sort
vehicles into the 13 FHWA vehicle classes (as identified in the FHWA Traffic
Monitoring Guide).

Determine the adequacy of automatic measurement of overall vehicle length.

Determine how the vehicle and axle sensor technology affects the accuracy of
the vehicle classification.

Determine the effects of vehicle repetitions, heavy axle loadings, and weather
on pneumatic tube axle sensors and other types of vehicle and axle sensors.

Multiple testing sessions are planned over an 18 month period with various AVC
accuracy characteristics being analyzed with respect to parameters such as vehicle speed,
traffic volume, pavement temperature and others.



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5.2.3 Peek Traffic Inc. GK-6000

The Peek Traffic Inc. model GK-6000 classifier was configured to monitor two lanes
each using a P-P sensor configuration and Philips Vibracoax axle sensors. Although
configured for two lanes, both sets of sensors were placed in the same lane of traffic (the
test lane). The results from both sets of sensors are presented below.

5.23.1 First 48-Hour Test

The classification matrices for the first 48 hour test and the summary of number of
vehicles (real and vendor), mistyped vehicles, sensor errors, extra vendor vehicles, missing
vendor vehicles, correctly classified vehicles, suspected splits and suspected combinations are
presented in Figures 34 and 35 for lanes 1 and 2, respectively. The classification matrix is
presented in both absolute numbers, and percentages. The classifier designated lane 1
correctly classified 73.7% of the vehicles (90.1% if class 2-3 errors not included). The
number of vehicle axles was miscounted 6.29% (percent sensor errors) of the time. The
classifier designated lane 2 correctly classified 77.1% of the vehicles (92.4% if class 2-3
errors not included). The number of vehicle axles was miscounted 4.02% (percent sensor
errors) of the time. Approximately 2.5% of the vehicles classified by either of the lanes
were the result of a suspect split or combination of an actual vehicle.

The measurement accuracy of the classifier as a function of vehicle speed is depicted
in Figures 36 and 37 for lanes 1 and 2, respectively. The GK-6000 classifier measures axles
spacings and wheelbase length. The measurement error statistics (mean and deviation) for
all measurements are included in the figure as a function of measured vehicle speed (mph).
Note that all measurements are in feet.

Tables VIN and IX contains a summary of the results of the classification accuracy
as a function of percent vehicles with greater than two axles, air temperature and pavement
temperature for lanes 1 and 2, respectively.



The evaluation site has traffic that includes all 13 of the FHWA classifications
except triple trailer units which are illegal in Georgia. The site is also acceptable for
conducting the "Extended Pneumatic Tube Testing" called for in Task F of the statement
of work.

The expressway was constructed in 1965 and was improved with an overlay in
1986. The pavement condition is fair with no cracking, dips or uneven areas; however,
there is some rutting present. The rutting is most severe at the beginning of the test
area (the east end of the site) at approximately 1/2 inch and decreases to approximately
1/4 inch at the end of the test area. It was decided that this amount of rutting is fairly
typical and should not be a problem.

2.1.3 Test Facilities and Instrumentation

A mobile field office was placed on the site to house personnel and equipment
during the tests. Power poles were installed, wires were run, and breaker boxes installed
by the local power company. Instrumentation required for the test included a video
camera for classification of vehicles (with lights for videotaping at night), a video camera
to record lane changes within the test area, air and pavement temperature recording
equipment, and a rainfall quantity sensor. The test instrumentation concept is shown in
Figure 1.

The classification camera was mounted near the mobile office on a pole which
was 69 feet from the outside edge of the test lane. The camera, in its fan-cooled
environmental enclosure, was mounted 40’ 4" above the level of the highway surface
resulting in a pointing angle of 30 degrees down from horizontal. This mounting gave a
sufficient angle of view to determine the position of the vehicle within the test lane. The
road was marked with reflective tape at ten foot intervals to allow for vehicle length
measurement. Two 1 kilowatt metal halide lights were mounted on the same pole
approximately 10 feet below the camera for videotaping at night. A VHS video cassette
recorder was located in the mobile office. The video was time stamped for correlation
with the classifier data and the lane change video.

The lane change camera was enclosed in a traffic control cabinet mounted on the
overpass for State Road 81, and the video cassette recorder was located in another
cabinet near the overpass, The. camera was mounted such that it was directly over the
center line of the westbound lanes and viewed the entire test area. The lane change
video was also time stamped for correlation with the classification video.

Temperature and rainfall measuring equipment were set up for each test instead
of being permanently installed. Temperatures were measured with thermocouple
thermometers, and rain was measured with a digital tilt-pan rain gauge.



Sensor Heights (inches)

INTERNATIONAL ROAD DYNAMICS, INC.

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5.2.11.3 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XXXII. The totals for the
entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the
first and last of the seven days.

Table XXXII. Long-Term Count/Classification Accuracy
Golden River Marksman 660

Grnd Truth i i Percent Percent

153



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Figure 48.



12. Participating AVC System Vendors

The FHWA provided the Georgia Department of Transportation (GaDOT} with a
list of vendors that had indicated a willingness to participate in the assessment project.
GaDOT and GTRI contacted each vendor to schedule equipment acquisition and testing.
The vendors were asked to specify equipment and sensor selections, configurations, and
installation procedures for maximum classification accuracy. Each vendor agreed to provide
the equipment to the project on a no-charge loan basis. Permanently installed sensors were
purchased by GaDOT directly from the AVC vendor assuring that each vendor was able to
select and provide the best sensor for his equipment.

A list of participating vendors (including addresses and points of contact) is included
as Appendix A. Tabie | lists the equipment configurations supplied for test by each vendor.
In the "Configuration" column, the "P" is a piezoelectric axle sensor, and the "L" is an
inductive loop vehicle presence sensor.

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Peek Traffic TrafiCOMP II- The vendor supplied a modified instruction set on
an EPROM which transmitted the vehicle-by-

vehicle data (the screen display) to a serial prot
on the unit. The serial port was connected to a
portable PC running a terminal emulator
program. Data was stored by using the logging
capability of the termina] emulator.

PAT Equipment AVC-100 - One of the PAT units (PAT 2) did not have the
internal memory to store the vehicle-by-vehicle
data. This unit was connected to a PC running a
monitoring program supplied by the vendor. The
program stored the data using a logging function.

The following is a list of the classifiers which, due to memory limitations, had to have data
downloaded to a PC during the detailed testing sessions:

e Peek GK-6000,

e Electronic Control Measure HESTIA,

e International Road Dynamics TC/C 530-4D/4P/4L,
e Golden River Traffic Marksman 660, and

e Diamond Traffic Products TT-2001.

The remaining classifiers had sufficient internal memory to store the vehicle-by-vehicle data

for the entire 48 hours of the detailed testing sessions.

Once the equipment was installed and checked out, the AVC equipment was turned
on and recording of the traffic begun. The internal clocks of the classifiers and the video
recorders were then synchronized. Each classifiers was checked to ensure proper operation.

The video recorders for the lane-change camera and the pole camera were started
once all the classifiers were operational. The starting of both camera marked the official
start of the test.

The test site was manned continually during the detailed (48-hour) testing periods.
The person manning the site changed the video tapes as needed, and downloaded the data
from the classifiers which required storage on the PC to avoid overflowing the internal
memory of the classifier. During the first 48-hour test, the air and pavement temperature
were measured manually, and the precipitation and wet/dry pavement conditions observed

46



MITRON SYSTEMS CORPORATION
2000 Century Plaza
Columbia, MD 21044

SALES REPRESENTATIVE
Donald A, Dixon (410) 992-7700
FAX (301) 596-5119

MODEL NAME
MSC 3000 Traffic Counter

GENERAL DESCRIPTION OF EQUIPMENT
Multi-lane vehicle classifier. Operates in binning mode. Operates with
inductive loops, piezoelectric sensors, and road tubes.

METHOD OF OPERATION
Unattended, data is retrieved with a separate unit, or via modem/PC (celluar

available).

METHOD OF DATA STORAGE
Battery-backed CMOS RAM portable Memory Pack

DATA STORAGE CAPACITY
8K standard, 10K optional; 32K for telemetry unit

VEHICLE CLASSIFICATION SCHEME
FHWA Scheme F capability; custom schemes available

POWER SOURCE
1 each 6 Volt, 12 amp-hr rechargeable and 4 ea. 1.5 V, C-size alkaline
batteries (solar or AC available)

OPERATING TEMPERATURE RANGE
-40°F to 176°F (Electronics)

OPERATING VEHICLE SPEED RANGE
0 to 99 mpb

DIMENSIONS AND WEIGHT OF EACH MAJOR COMPONENT
12" x 10" x 6.5” painted stainless steel housing - 26 Ibs

MAXIMUM LENGTH OF LEAD CABLE
Loop - 800’; Piezo - depends upon the type; Road Tube - 15’ to 200’,
depending on the traffic

PURCHASE COST OF EQUIPMENT
$739 to $1600

203



axles Spacing Statistics Length Statistics

Speeds Mean $10 Veh = Axte_Spacings Speeds Mean STD Vehicles
0.660 1.146 48 34 30 2.703 3.139 48
30.0-34.9 9.000 0.000 o ° 30.0-34.9 0.000 0.000 0
35.0-39.9 0.560 0.000 4 1 35.0-39.9 0.100 0.000 1
40.0-64.9 0.113 0.082 3 6 40.0-44.9 0.203 1.020 3
45.0-49.9 0.095 0.574 2 47 45.0-49.9 0.265 2.049 27
50.0-56.9 0.127 0.385 154 50.0-54.9 0.536 1.485 154
$5.0-59.9 0.112 0.49% S79 1174 55.0-59.9 0.565 1.506 579
$0.0-66.9 0.096 0.899 1177 2328 60.0-64.9 0.590 1.808 1177
65.0-69.9 0.126 0.655 946 437 65.0-69.9 0.684 2.954 946
70.0-7%6.9 0.206 0.654 258 303 70.0-74.9 0.785 1.256 258
%5.0-79.9 0.155 0.304 4s 48 75.0-79.9 0.602 1.260 45
80 0.602 0.770 6 6 80 1.795 2.068 6
Overall 0.120 0.732 3244 S740 Overall 0.598 2.157 3204

wean STD «= Vehicles sip Vehicles
0.742 1.205 4s 32.30 48
0.000 0.000 ) 0.000 °
0.540 0.000 1 0.030 1
0.227 0.231 3 2.927 3
0.163 0.973 27 6.272 27
0.273 (0.572 154 5.16 154
0.221 0.667 579 6.205 579
0.182 = 1.308 we 6.168 V77
0.189 0.796 946 7.646 946
0.238 «0.699 Be 6.973 258
0.165 0.325 45 6.305 45
0.602 0.770 6 W13.24 15.49 6
0.209 0.990 3244 Overalt 102.95 8.25 3266

Figure 47. Measurement Accuracy Versus Speed (MPH)
ECM HESTIA - 1st 48-Hour Test

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Table XII. Long-Term Count/Classification Accuracy

Peek GK-6000 (Lane 2)

i Class 4 | 87 305 +218 28.52 24,14 246.62
i Class 5 1399 1080 319 129.54 80.79 137.25
Class 6 | 589 538 51 109.48 100.92 107.83
Class 7 | 6 49 ~43, 12.24 40.00 20.00
Class 8 735 808 -73 90.97 96.58 93.30
Class9 8101 TIL 340 104.38 106.80 101,92
Class 10 L 96 68 2 141.18 175.00 130.77
Class 11 215 200 15 107.50 125.71 102.27

99



Piezo-Electric
Data Sheet No. 1

Tl Golden River Instraments, Enc,
7352 Dartford Drive,. #7,
McLean, Virginia 22102

Tel 703 847 66,5 :ax 703 847 5648
Single Piezo-electric Cable Sensor

CZ CLL iL ltiLe

YY)

iS La Piazo-electric cable

—-—— EPDM housing

LLL.

Construction

The sensor comprises a rubber extrusion developed by TRAFFIC 2000 for direct bonding into a road:
surface. Made from high-performance EPDM, it is impervious to attack from acids, alkalis, salts and
ultraviolet, This extrusion houses a pressure-sensitive co-axial cable which produces a voltage when
compressed or deformed by impact. The output is used to operate a wide variety of measurement and
analysis equipment.

Applications

@ A single sensor is used directly for axle counting, enabling simple traffic flow data to be obtained.
It also acts as a vehicle detector for car park barrier actuation or security control. It is sensitive to
all classes of vehicles, and the output can be used to give an indication of ade weight.

@ In conjunction with an inductive-loop presence detector, a single piezo-electric sensor will allow
further information to be deduced, such as the number of axles per vehicle.

@ Two sensors placed in the road at a known distance apart give a very accurate means of speed
TMmeasurement. This information is of value in traffic flow surveys, and is also used for speed limit
enforcement purposes. Red light violation is detectable, the sensors being used to trigger a camera
and to add a speed reading to the photograph.

@ If an inductive-loop detector is used with a pair of sensors, complete vehicle classification is
possible. This arrangement enables the wheelbase or axle spacing of each vehicle to be calculated,
in addition to its speed and approximate weight.

@ For some speed law enforcement purposes, two or even three speed measurements are required.
In these cases three sensors in parallel are sufficient, allowing a simple and cost-cffective
installati

@ Other groupings of two or three sensors in various arrays are used to obtain data on, for example,
the position of vehicles across the carriageway, width of vehicle, and transverse weight distribution.

TRAFFIC 2000 LIMITED
3 Church Terroce, Richmend, Surrey TWIO 6SE
Tel: 0819486736 Fex: 0813320813



5.2.4.1 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification
accuracy, vehicle count and axle count are summarized in Table XIV. The totals for the
portion of the seven days recovered for the vendor and classifier are listed. Also, the
difference (ground truth minus vendor) and the percent difference (ground truth * 100 /
classifier) are listed. To assess the change inaccuracy over the seven days, the percent
difference is calculated for the first and last of the seven days. Since only a portion of the
test data was recovered, the first day listed in the table refers to 12:45 pm on 9-13-93
through 10:45 am on 9-14-93, and the last day refers to 4:15 pm on 9-15-93 to 4:15 pm on
9-16-93,

Table XIV. Long-Term Count/Classification Accuracy
PAT AVC-100 (P-L-P)

Total Total Total Total 1st Day Last Day
Grnd Truth {| Classifier Difference Percent Percent Percent

Vehicles 39400 44537 -5137 88.47 101.87 101.92
Axles 104608 N/A N/A N/A N/A N/A
Class 1 60 18 42 33333 200.00 240.00
Class 2 18062 14334 3728 126.01 72.42 74.76
Class 3 11417 (2467 8950 462.79 261.15 262.70
Class 4 76 29 47 262.07 109.09 133.33
Class 5 1161 435 7h 266.90 225.00 197.74

| Class 6 458 286 172 160.14 113.00 113.76
Class 7 5 4 1 125.00 100.00 -
Class 8 620 1791 -1171 34.62 25.70 26.63
Class 9 7196 3824 3372 188.18 131.43 131.09
Class 10 84 24 60 350.00 257.14 212.50
Class 11 201 112 89 179.46 120.00 132.35
Class 12 60 33 27 181.82 120.00 144,44
“Class 13 0 16 -16 0.00 0.00 0.00
Class 15 0 21164 -21164 0.00 0.00 0.00

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of the axle sensors. The ability of the equipment to accurately classify vehicles was linearly
dependent on the ability of the sensor and classifier to accurately count the number of axles.
Therefore, performance of the piezoelectric axle sensor and the interface electronics in the
classification equipment are the primary factors effecting the accuracy of the equipment.

A further opportunity has arisen to collect more data concerning the performance of
these classification equipments. Road construction is under way at the test site and will
result in the sensors in the roadway being overlaid as part of a widening of the road. This
presents an opportunity to test the performance of the devices after a pavement overlay.
This issue is important to the maintainability of a traffic monitoring site. The results of the
overlay tests will be reported in and addendum to this report.



Table V. Accuracy Summary for Peek Traficomp III
ist 48-Hour Test

Pav Temp
60- 69 472 11.6 913 0.148 | 0.483 * . * *
1-79 | 4.19 TIS |} 928 0.171 | 0.380
g0-89 | 3.96 TIA 938 0.174 | 0.373
90-99 | 3.66 BS 92.6 0.161 } 0.248
100-109 | 239 76.0 95.0 0.181 | 0.296

3.52 76.7 93.4 0.177 | 0.508
- Does Not Measure C

110-119

78

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evaluation. The installed sensor element profile in Figure 10 shows that the elements
protrude above the channel slightly (+0.05 to +0.14 inches) and conform fairly well to the

toad surface.



Table XXVIII. Accuracy Summary for IRD TC/C 530-4D/4P/4L

@-L-P) Ist 48-Hour Test

Correct
(no 2,3)

Air Temp
50-59 8.41 653 89.4 0.125 | 0.634 | -2.083 8.809 93.47 | 39.51
O69 13.16 67.2 8 0115 | 1.000} -1340 | 12.084 99.56 | 54.97
70-79 8.86 69.3 879 0.134 | 0.492 | -1.065 | 12.023 | 100.19 | 55.55
80-89 3.00 75.2 93:8 0.151 | 0.680 | -0.845 | 11.571 | 100.76 | 54.41
Pav Temp
60- 69 13.79 623 83.5 0.117 | 0.791 | -2.017 9.423
70- 79 11.39 68.6 853 0.115 | 1.020 | -1.177 | 12302
80- 89 10.06 68.2 86.9 0.108 | 0.502 | -0.946 | 12.244
90- 99 6.57 13 90.0 0.140 | 0.431 | -1207 | 12.256
94.4 0.157 | 0.482 | 0.795 | 12.171
110-119 93.7 0.156 } 0.818 | -6.785 } 10.907
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143



525.3 Seven-Day Test

The results of the 7-day test to determine long-term statistics on classification

aceiracy vehicle count and axle count are summarized in Table
accuracy, vehicle count and axle count are summarized in Table XVM. The totals for the

entire seven days for the vendor and classifier are listed. Also, the difference (ground truth
minus vendor) and the percent difference (ground truth * 100 / classifier) are listed. To
assess the change inaccuracy over the seven days, the percent difference is calculated for the
first and last of the seven days.

Table XVI. Long-Term Count/Classification Accuracy
PAT AVC-100 (L-P-L)

Total
Difference

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Classification Matrix for Peek GX-6000 (Lane 1)

Figure 34.

ist 48-Hour Test
85



2.3.5 Electronic Controt Measure

ECM installed a mode) HESTIA classifier with ECM piezoelectric axle sensors (part
number PB2N33/25). The sensor layout is shown in Figure 11. The rutting at the location
of both axle sensors was 6/32 inch. The installation was performed on 12/10-11/92. It was
lightly raining and 47° F on the morning of the 10th; the asphalt cutting was done that
afternoon after the rain stopped. On the 11th, when the sensor was installed, it was partly
cloudy, 47° F, and windy.

The general axle sensor installation procedures were followed. The slots were cut
one day, but because of the rain, the installation could not be completed. The slots were
filled with sand and one turn of loop wire was installed in the loop cuts to protect them.
The next day the loop wire was pulled from the cuts to clean out any debris, and the sand
was cleaned out of the sensor slots. The slots were washed out, dried and preheated with
torpedo heaters. Two layers of duct tape was used along the top of the slot. The epoxy
used was ECM proprietary. The sensors were installed using 11 leveling plates, and since
the sensors were flexible, good conformity to the rutting profile was achieved. Because of
their flexibility, the sensors are always kept in an aluminum channel to protect them from
bending and possible damage until they are installed. Sufficient epoxy was poured such that
when the sensor was placed in the slot, epoxy was forced out. The epoxy was then smoothed
with a putty knife. Weights were placed on the plates to hold the sensor in place until the
epoxy starts to harden. The plates were then removed, and the epoxy was heated using
torpedo heaters and a full length cardboard tunnel until completely cured. The installed
sensor element profiles in Figure 12 show that these sensors are nearly level with the
pavement and conform very well to the rutting.

Loop measurements indicated 139 microhenries and good stability. Initial tests of
the axle sensors with an oscilloscope indicated outputs slightly lower than desired by the
vendor and somewhat erratic for one sensor. The number one sensor frequently gave
negative output voltages, low voltages, and occasionally missed axles completely. The
number two sensor output was low but fairly consistent. Sensor number one was later
replaced. The replacement procedure involved cutting the old sensor out with multiple
passes of the asphalt saw. All of the sensor was removed and most of the old epoxy. The
same installation procedure was used for the new sensor. The new sensor was slightly
different in that it was manufactured with molded-in metallic strips to limit the flexibility
and protect the sensor from bending damage.

After the sensor replacement, the classifier was functional but missed too many
vehicle axles due to low sensor output levels. In order to get acceptable signals, strips of
bituthane tape approximately one inch wide were placed over the entire length of both
sensors. The classifier was then approved by the vendor for testing.