Appendix V: Development of Data Acquisition System (DAS)

In evaluating the data acquisition needs, an evaluation of existing
DAS's was conducted. It was determined through the study that no
commercial or government developed system (including DASCAR) was
available that would meet all the performance requirements. PATH
therefore designed a system that is composed of two distinct systems -
one system records engineering data and the other records video data.
The engineering data is recorded with a PC based computer. The computer
used is an Industrial Computer Systems 9300™ series bench top computer
using ISA/PCI architecture. This computer records the output from a
variety of sensors. The sensors selected by PATH to capture the
environment around the bus include commercially available mono-pulse
millimeter-wave radars and scanning infrared lasers. Both the radar and
scanning laser measure distance and azimuth angle for multiple targets.
The radar units are mounted on the front bumper, one on each end,
pointing forward. Ultrasonic sensors were originally used as corner
sensors, however they did not work well for two reasons. Firstly, the
ground was being picked up as a target as the sensitivity was adjusted
to a high level. Secondly, as ultrasound transceiver surface was not
water proof it was decided that they were not appropriate as corner
sensors. It was then decided that Denso LIDAR sensors would be better
for this role, so several of these were acquired from Denso. Three lidar
units are mounted on the bumper. The units mounted at each end of the
bumper are pointing out 20 degrees and the one mounted near the center
is pointing straight ahead. Other sensors record the driver inputs to
the bus, such as steering wheel angle, brake line pressure, throttle
position, and turn signal activation. Other sensors include an
accelerometer and a GPS system. The radars, lidars, and GPS data are
recorded using RS232 communication protocol. The remaining sensors are
recorded using an analog to digital board and anti-aliasing filters.

  -----------------------------------------------------------------------
  ![](media/image1.jpeg){width="3.9229166666666666in"
  height="2.9923611111111112in"}

  Fig. 1 Sensors installed on a bus
  -----------------------------------------------------------------------

Video data is recorded using a commercially available digital video
system. The first digital video recording system implemented saved the
video as a series of still images in an encrypted proprietary format.
This limited the level of compression and allowed only three days of
data to be collected before the removable hard disks had to be changed.
This also required that the video data first be converted to a standard
still-picture format, and then be converted to a standard moving-picture
format (MPEG-1). This was a very time consuming manual process. The
video recorder was not reliable such that it crashed the flash-ROM
system several times. A Loronix™ video system was found that offered
several improvements over the previous system. This system records video
in a standard still format (AVI) and allows for automated conversion to
MPEG-1 format. Much less time is required to convert the video data now
that the process is automated. The system also has greater storage
capacity than the previous one, allowing one week of data collection
before the removable hard disks need to be changed. This system was
retrofitted on the first bus and has proven to be much more reliable and
easier to use. The video cameras in the originally developed system were
too obtrusive, and easily damaged or moved by passengers. A different
style of video camera was selected to replace them. These cameras have a
form factor that allowed them to be installed in the destination window
of the bus. This makes them less obtrusive and prevents them from being
tampered with. This system records up to six cameras in AVI format onto
a PC hard drive. Four miniature "board cameras" capture video images
around the bus. The cameras capture the front road scene, the left and
right front corner road scene, and the passenger compartment of the bus.
The video streams from the four cameras are combined into one video
stream by a quad image combiner to extend the hard drive storage
capacity.

Synchronization between engineering and video data is very important for
later playback. The first item of information for synchronization is the
time stamp recorded in the video frame as a title. This time stamp is
generated by a title generator which receives the clock time from the
engineering computer. This title allows for manual synchronization. The
engineering computer also sends three synchronization signals to the
video recorder through the alarm inputs. These signals and their
triggering time stamps are recorded separately by both the engineering
computer and the video recorder. The signals are triggered every one
minute, 15 minutes and 60 minutes respectively. By matching the signal
records in the engineering data with the records of alarms in the video
recorder, time difference between the two computers can be determined.
Once the computer time difference is matched, the video clips can be
synchronized with the engineering data streams. The synchronization
occurs as part of the process of transferring the data from the
removable hard disks to a permanent data base storage system. The
permanent data base storage system is composed of a Redundant Array of
Inexpensive Disks (RAID). Once the data base has been synchronized and
broken into small data clips each set of data clips is saved in one
folder for easy access.

  -----------------------------------------------------------------------
  ![](media/image2.wmf){width="5.499305555555556in"
  height="1.9993055555555554in"}

  Fig. 2 System layout on the bus
  -----------------------------------------------------------------------

The data acquisition system has been installed on three buses in the
SamTrans fleet. A fourth system has been prepared for installation on a
yet to be determined bus from another agency in the Bay Area. The first
system started collecting data in August 2000. The second system started
collecting data in April 2001. After the second system started running,
the first system was updated with the new design. The third bus started
collecting data in January 2002.

## Calibration of DAS {#calibration-of-das .Style-Heading-2-+-Justified-Left:--0\"-First-line:--0\"-Before:--1...}

The location and direction of some sensors will influence the system
performance. Before running the bus out to collect data, the sensors and
the entire system must be calibrated. The calibration process involves
the following three tasks: 1) measure the location and direction of the
sensors, 2) correct the location and direction of some sensors, and 3)
examine the system alignment.

This section describes the calibration process of the first DAS on the
first bus and gives the results. The 1^st^ section gives the
measurements of location and sensor direction. The 2^nd^ section
describes the laser radar calibration procedure and results. The 3^rd^
section describes the calibration approaches for cameras. Calibration of
system alignment is given in the 4^th^ section. Calibration of other
sensors is given in the 5^th^ section. The DAS design was changed after
the first DAS was calibrated. However, the calibration process and the
techniques presented in this document were conducted to calibrate all
the systems. For convenience, the following abbreviations are used.

  --------------------------------------- -------------------------------
  Table 1 DAS calibration abbreviations   

  *Sensor Name*                           *Abbreviation*

  passenger side corner camera            P-CAM

  front-looking camera                    F-CAM

  driver side corner camera               D-CAM

  passenger side upper ultra-sensor       UP-SONAR

  passenger side lower ultra-sensor       LP-SONAR

  passenger side radar                    P-RADAR

  laser radar                             LIDAR

  front-looking ultra-sensor              F-SONAR

  driver side radar                       D-RADAR

  driver side upper ultra-sensor          UD-SONAR

  driver side lower ultra-sensor          LD-SONAR

  Interior-looking camera                 I-CAM

  rear-looking camera                     R-CAM

  rear radar                              R-RADAR

  global positioning system               GPS
  --------------------------------------- -------------------------------

Sensor position

Coordinate systems

To locate the sensors, two reference frames were built on the bus. One
is the Front Coordinate System (FCS) and the other is the Rear
Coordinate System (RCS). Locations of front sensors, including P-CAM,
F-CAM, D-CAM, UP-SONAR, LP-SONAR, P-RADAR, LIDAR, F-SONAR, D-RADAR,
UD-SONAR, LD-SONAR and I-CAM, are measured in the FCS. Locations of rear
sensors, including R-CAM, R-RADAR and GPS are measured in the RCS. The
reference points of the coordinates and the positions of the sensors are
illustrated in the following figures. The positive x-axis is
horizontally to the left, the positive y-axis is vertically upward, and
the positive z-axis is horizontally to forward. The basic dimensions of
the bus are: length = **12200** mm, width = **2750** mm.

Front Sensors

The reference point of the FCS and the locations of the front sensors
are illustrated in Fig. 3.

  -----------------------------------------------------------------------
  ![](media/image3.wmf){width="4.8125in" height="2.875in"}

  Fig. 3 FCS and front sensors
  -----------------------------------------------------------------------

The reference point is on the front center of the bus. The height of the
reference point from the ground is **585**mm. The coordinates of the
front sensors are listed in the following table.

Table 2 Front sensor locations

+------------------+----------+---------+---------+------------------+
| 1.  **Sensors**  | 2.  **x  | 3.  **y | 4.  **z | 5.  **Angle      |
|                  |          |         |         |     (Deg)**      |
|                  |   (mm)** |  (mm)** |  (mm)** |                  |
+------------------+----------+---------+---------+------------------+
| 6.  LIDAR        | 7.  -836 | 8       | 9.  78  | 10. ^1^N.A.      |
|                  |          | .  -195 |         |                  |
+------------------+----------+---------+---------+------------------+
| 11. P-RADAR      | 1        | 1       | 14. 70  | 15. N.A.         |
|                  | 2. -1050 | 3. -132 |         |                  |
+------------------+----------+---------+---------+------------------+
| 16. UP-SONAR     | 1        | 18. -97 | 19. 64  | 20. ^2^-36       |
|                  | 7. -1201 |         |         |                  |
+------------------+----------+---------+---------+------------------+
| 21. LP-SONAR     | 2        | 2       | 24. 64  | 25. ^2^-26       |
|                  | 2. -1201 | 3. -176 |         |                  |
+------------------+----------+---------+---------+------------------+
| 26. D-RADAR      | 27. 985  | 2       | 29. 67  | 30. N.A.         |
|                  |          | 8. -135 |         |                  |
+------------------+----------+---------+---------+------------------+
| 31. UD-SONAR     | 32. 1190 | 33. -95 | 34. 64  | 35. ^2^35        |
+------------------+----------+---------+---------+------------------+
| 36. LD-SONAR     | 37. 1190 | 3       | 39. 64  | 40. ^2^26        |
|                  |          | 8. -175 |         |                  |
+------------------+----------+---------+---------+------------------+
| 41. F-SONAR      | 42. 790  | 4       | 44. 61  | 45. N.A.         |
|                  |          | 3. -161 |         |                  |
+------------------+----------+---------+---------+------------------+
| 46. D-CAM        | 47. 396  | 48. 991 | 49. -80 | 50. ^3^14        |
+------------------+----------+---------+---------+------------------+
| 51. F-CAM        | 52. -69  | 5       | 54. -61 | 55. ^3^13        |
|                  |          | 3. 1653 |         |                  |
+------------------+----------+---------+---------+------------------+
| 56. P-CAM        | 57. -109 | 5       | 59. -95 | 60. ^3^25        |
|                  |          | 8. 1563 |         |                  |
+------------------+----------+---------+---------+------------------+
| 61. I-CAM        | 62. -409 | 6       | 6       | 65. N.A.         |
|                  |          | 3. 2186 | 4. -365 |                  |
+------------------+----------+---------+---------+------------------+

66. *1: N.A. = Not available;*

67. *2: These are azimuth angles;*

68. *3: These are tilting angles.*

Rear Sensors

The reference point of the RCS and the locations of the rear sensors are
illustrated in Fig. 4.

  -----------------------------------------------------------------------
  ![](media/image4.wmf){width="4.8125in" height="3.625in"}

  Fig. 4 RCS and rear sensors
  -----------------------------------------------------------------------

The reference point is on the rear center of the bus. The height of the
reference point to the ground is **790**mm. The coordinates of the rear
sensors are listed in the following table.

Table 3 Rear sensor locations

+-------------------+---------+---------+---------+-------------------+
| 69. **Sensors**   | 70. **x | 71. **y | 72. **z | 73. **Angle       |
|                   |         |         |         |     (Deg)**       |
|                   |  (mm)** |  (mm)** |  (mm)** |                   |
+-------------------+---------+---------+---------+-------------------+
| 74. R-RADAR       | 75. 950 | 7       | 77. -39 | 78. ^1^N.A.       |
|                   |         | 6. -154 |         |                   |
+-------------------+---------+---------+---------+-------------------+
| 79. GPS           | 80. 590 | 8       | 82. 800 | 83. N.A.          |
|                   |         | 1. 2220 |         |                   |
+-------------------+---------+---------+---------+-------------------+
| 84. R-CAM         | 85. 500 | 8       | 87. 140 | 88. ^2^16         |
|                   |         | 6. 1500 |         |                   |
+-------------------+---------+---------+---------+-------------------+

89. *1: N.A. = Not available;*

90. *2: Tilting angle.*

#### LIDAR calibration {#lidar-calibration .LABEL}

#### Optical axis orientation {#optical-axis-orientation .LABEL}

The LIDAR beam is scanning in 2D by rotating a hexagon mirror. The
equivalent detection scope is 16 degrees in horizontal and 4.4 degrees
in the vertical direction. The equivalent optical axis is defined to
originate from the LIDAR lens extending to the center of the detection
scope, i.e. eight degrees to both the left and the right margins and 2.2
degrees to both the top and the bottom margins. There are two adjustable
screws on the front face of the LIDAR, which can be rotated to adjust
the optical axis in 2D (both horizontal and vertical directions). As the
LIDAR has been mounted on the passenger side on the 1^st^ bus, to
calibrate the LIDAR, we must first adjust the optical axis to an
appropriate direction \[1\].

The LIDAR optical axis is set horizontally to the point on the bus's
longitudinal center line, 50 meters away from the bus front reference
point, and vertically 2.2 degrees up with respect to the horizontal
plane. The geometric relationship is illustrated in Fig. 5.

  -----------------------------------------------------------------------
  ![](media/image5.wmf){width="5.7in" height="1.2in"}

  Fig. 5 LIDAR calibration geometry
  -----------------------------------------------------------------------

#### LIDAR calibration procedure {#lidar-calibration-procedure .LABEL}

91. LIDAR calibration was done by the following procedure.

1\. Measure LIDAR lens vertical position (height to ground) **H
=[\_*0.425*\_\_]{.underline}**(m).

2\. Measure **R=[\_50m\_]{.underline}** from bus front reference point
along the longitudinal direction.

3\. Set the reflector at ***R=50m*** with vertical position = **H**.

4\. Adjust both the lower and the higher screws simultaneously, make
reported "lateral position" = \_\_[0\_\_]{.underline}. Change lateral
position to check the adjustment.

Table 4 LIDAR lateral position test

  ------------------- ------------------------- -------------------------------------
  Actual lateral      Expected report number    LIDAR report (5^th^ col)
  position                                      

  6m Left             -60 \*.1m                 *[\_\_\_\_\_-61\_\_\_]{.underline}*

  3m Left             -30 \*.1m                 *[\_\_\_\_\_-30\_\_\_]{.underline}*

  3m Right            30 \*.1m                  *[\_\_\_\_\_30\_\_\_]{.underline}*

  6m Right            60 \*.1m                  *[\_\_\_\_\_61\_\_\_]{.underline}*
  ------------------- ------------------------- -------------------------------------

5\. Adjust the lower screw, make reported "Vertical Position" changing
from smaller to larger numbers thru \_\_[12\_\_]{.underline}.

6\. Adjust the lower screw to " -- direction"
\_\_[0.3-0.5\_\_]{.underline} rev, make sure that the LIDAR keeps
detecting the reflector.

7\. Change distance to check the adjustment:

Table 5 LIDAR range test

  ------------------ ------------ ------------ ---------------------------------- --------------------------------
  Actual distance    Expected                  LIDAR report (1^st^-2^nd^ col)     
                     report                                                       
                     number                                                       

  40m                31\*1.28m    32\*.01m     [\_*31*\_\_]{.underline}\*1.28m    [\_*98*\_\_]{.underline}\*.01m

  30m                23\*1.28m    56\*.01m     [\_*24*\_\_]{.underline}\*1.28m    [\_*14*\_\_]{.underline}\*.01m

  20m                15\*1.28m    80\*.01m     [\_*16*\_\_]{.underline}\*1.28m    [\_*48*\_\_]{.underline}\*.01m

  10m                7\*1.28m     104\*.01m    [\_*8*\_\_\_]{.underline}\*1.28m   [\_*46*\_\_]{.underline}\*.01m
  ------------------ ------------ ------------ ---------------------------------- --------------------------------

8\. Put the reflector at ***R=10m***, with vertical position changing,
check the adjustment:

Table 6 LIDAR vertical position test

  ----------------------- ----------------------- ---------------------------------
  Actual vertical         Expected report number  LIDAR report (9^th^ col)
  position                                        

  H+0.76m                 2                       [\_\_*2*\_\_\_\_\_]{.underline}

  H+0.57m                 3-4                     [\_\_*4*\_\_\_\_\_]{.underline}

  H+0.38m                 6-7                     [\_\_*5*\_\_\_\_\_]{.underline}

  H+0.19m                 9-10                    [\_\_*6*\_\_\_\_\_]{.underline}

  H+0m                    12                      [\_\_*8*\_\_\_\_\_]{.underline}
  ----------------------- ----------------------- ---------------------------------

#### Camera calibration  {#camera-calibration .LABEL}

#### Rough adjustment {#rough-adjustment .LABEL}

Three different options of focal length are available: 3mm, 4mm, and
7.5mm. Lenses with different focal length were fitted on the camera
heads. Comparing the field of view and selecting the one list that best
matches the area of interest around the bus, the optimal fitted focal
length was chosen for each camera, as in the following table.

Table 7 Focal length of cameras

  ------------------------------------------ ----------------------------
  Camera                                     Focal length

  D-CAM                                      4mm

  F-CAM                                      7.5mm

  P-CAM                                      4mm

  I-CAM                                      4mm

  R-CAM                                      7.5mm
  ------------------------------------------ ----------------------------

Image plane rotation and optical axis direction of each camera was
roughly adjusted by monitoring the video output. The factors of interest
while adjusting are: range coverage, azimuthal direction of interest,
and consistency between adjacent cameras. The tilting angle of each
camera was measured with a level and an angle measure.

#### Intrinsic and extrinsic parameters calculation {#intrinsic-and-extrinsic-parameters-calculation .LABEL}

##### Control points {#control-points .unnumbered}

To calibrate the cameras, 20 control points arranged in 4 lines with 5
points in each line were made on a vertically standing black screen. The
adjacent lines are 50 centimeters apart. The distance between adjacent
points in each line is also 50 centimeters. The screen was put in front
of each camera with the points facing the camera. A picture was taken
and stored in the computer. The screen was then moved 25 centimeters
(for F-CAM and R-CAM) or 20 centimeters (for D-CAM and P-CAM) closer to
the camera. This process was repeated until five pictures were taken for
each camera. Every time a picture was taken, the position of the screen
in the bus coordinate system was marked on the ground and measured later
to calculate the control point coordinates.

The pictures were opened in Microsoft Photo Editor™ to read the image
coordinates of the control points. We get the coordinates of the control
points in the bus coordinate system and their corresponding image
coordinates in the picture. Each control point and its image are called
a calibration pair. By substituting the coordinates of the calibration
pairs in the camera model described below, two equations for each pair
were obtained. We can solve the unknown camera parameters from the
equations for all pairs in the sense of Least Square Error (LSE).

Camera model

Let ![](media/image6.wmf){width="1.0in" height="0.2638888888888889in"}
represent the coordinates of a point in the bus coordinate system (FCS
or RCS), ![](media/image7.wmf){width="1.3194444444444444in"
height="0.2777777777777778in"} represent the coordinates of the point in
the camera coordinate system,
![](media/image8.wmf){width="0.6111111111111112in" height="0.25in"} and
![](media/image9.wmf){width="0.6111111111111112in"
height="0.2361111111111111in"} represent the undistorted and distorted
image coordinates of the point respectively, and
![](media/image10.wmf){width="0.3611111111111111in"
height="0.2222222222222222in"}represent the coordinate read in Microsoft
Photo Editor™, i.e. the pixel location with respect to the top-left
corner in the image, viz. the computer image coordinate. The
relationship between the bus coordinate system and the camera coordinate
system is given by \[2\]:

![](media/image11.wmf){width="0.8888888888888888in" height="0.25in"} (1)

where ![](media/image12.wmf){width="0.5694444444444444in"
height="0.2638888888888889in"} is a 3×3 ortho-normal rotation matrix
defining the camera orientation and
![](media/image13.wmf){width="0.9722222222222222in"
height="0.2777777777777778in"} is a translation vector defining the
camera position. The camera coordinate system is transformed to the
undistorted image coordinate (2D) system according to the pin-hole
model:

![](media/image14.wmf){width="0.9027777777777778in" height="0.94375in"}
(2)

where ![](media/image15.wmf){width="0.16666666666666666in"
height="0.2222222222222222in"} is the focal length. The distortion of
image coordinates can be modeled by \[4\]:

![](media/image16.wmf){width="2.763888888888889in"
height="0.5555555555555556in"} (3)

where ![](media/image17.wmf){width="0.9166666666666666in"
height="0.2638888888888889in"}, ![](media/image18.wmf){width="0.44375in"
height="0.2361111111111111in"}are coefficients of tangential distortion,
and![](media/image19.wmf){width="0.16666666666666666in"
height="0.2361111111111111in"} is the coefficient of radial distortion.
The distorted image coordinates are then obtained:

![](media/image20.wmf){width="1.0416666666666667in"
height="0.5277777777777778in"} (4.1)

or

![](media/image21.wmf){width="3.1527777777777777in"
height="0.5277777777777778in"} (4.2)

The relationship between the distorted image coordinates and the
computer image coordinates is given by:

![](media/image22.wmf){width="1.2083333333333333in"
height="0.5277777777777778in"} (5)

where ![](media/image23.wmf){width="0.4861111111111111in"
height="0.2638888888888889in"} are the distance between the adjacent
imaging sensor elements in rows and columns, respectively,
![](media/image24.wmf){width="0.4861111111111111in" height="0.25in"}
represents the computer image coordinate of the principal point of the
image coordinate system.

The model itself is a nonlinear one. The unknown parameters can be
categorized into intrinsic and extrinsic, or linear and non-linear
parameters, as follows:

Table 8 Parameter table

  --------------- ------------------------------------------------------------------------------------ -------------------------------------------------------------------------
                  Linear                                                                               Nonlinear

  Intrinsic       ![](media/image15.wmf){width="0.16666666666666666in"                                 ![](media/image19.wmf){width="0.16666666666666666in"
                  height="0.2222222222222222in"},![](media/image25.wmf){width="0.4861111111111111in"   height="0.2361111111111111in"},![](media/image18.wmf){width="0.44375in"
                  height="0.2638888888888889in"},![](media/image24.wmf){width="0.4861111111111111in"   height="0.2361111111111111in"}
                  height="0.25in"}                                                                     

  Extrinsic       ![](media/image26.wmf){width="0.94375in"                                             
                  height="0.2916666666666667in"},![](media/image13.wmf){width="0.9722222222222222in"   
                  height="0.2777777777777778in"}                                                       
  --------------- ------------------------------------------------------------------------------------ -------------------------------------------------------------------------

Calibration procedure

It is hard to solve all the parameters simultaneously from the complete
nonlinear camera model. However, if the nonlinear distortion can be
neglected, the model becomes linear. Once the linear parameters are
known, the nonlinear parameters can be solved from linear equations (3).
These properties of the camera model help us to simplify the calibration
procedure into the following steps \[3\]:

Step 1: Assume no distortion, calculate linear model parameters

Step 2: Calculate distortion using the linear parameters estimated in
Step 1

Step 3: Calculate nonlinear parameters using the distortion and linear
parameters estimated in Step 2

Step 4: Calculate distortion using the linear and nonlinear parameters
estimated in Step 2 and 3

Step 5: Subtract the distortion estimated in Step 4 from the image
coordinates, loop to Step 1 or terminate

The procedure is terminated when it is convergent. As noise exists in
the calibration pair coordinates, the distortion used in Step 5 was
multiplied with a positive fraction to confirm convergence. The positive
fraction used in our calculation is 0.999.

Calibration results

Control point images

Control point image coordinates estimated with linear-only and
nonlinear-plus models together with the actual image coordinates read in
Photo Editor™ are illustrated in the following plots, where the 'o'
signs represent the actual images read in Photo Editor™, the '+' signs
represent the images estimated only with linear model, and the 'x' signs
represent the images estimated with linear plus nonlinear model.

+-----------------------------------+-----------------------------------+
| ![](media/image27.                | ![](media/image28.                |
| wmf){width="2.9166666666666665in" | wmf){width="2.9166666666666665in" |
| height="2.1875in"}                | height="2.1875in"}                |
|                                   |                                   |
| F-CAM                             | D-CAM                             |
+-----------------------------------+-----------------------------------+
| ![](media/image29.                | ![](media/image30.                |
| wmf){width="2.9166666666666665in" | wmf){width="2.9166666666666665in" |
| height="2.1875in"}                | height="2.1875in"}                |
|                                   |                                   |
| P-CAM                             | R_CAM                             |
+-----------------------------------+-----------------------------------+
| Fig. 6 Control point images       |                                   |
+-----------------------------------+-----------------------------------+

Distortion

Distortion is calculated and plotted in the following plots.

+-----------------------------------+-----------------------------------+
| ![](media/image31.                | ![](media/image32.                |
| wmf){width="2.9166666666666665in" | wmf){width="2.9166666666666665in" |
| height="2.1875in"}                | height="2.1875in"}                |
|                                   |                                   |
| δx of F-CAM                       | δx of D-CAM                       |
+-----------------------------------+-----------------------------------+
| ![](media/image33.                | ![](media/image34.                |
| wmf){width="2.9166666666666665in" | wmf){width="2.9166666666666665in" |
| height="2.1875in"}                | height="2.1875in"}                |
|                                   |                                   |
| δx of P-CAM                       | δx of R-CAM                       |
+-----------------------------------+-----------------------------------+
| Fig. 7 δx of four cameras         |                                   |
+-----------------------------------+-----------------------------------+

+-----------------------------------+-----------------------------------+
| ![](media/image35.                | ![](media/image36.                |
| wmf){width="2.9166666666666665in" | wmf){width="2.9166666666666665in" |
| height="2.1875in"}                | height="2.1875in"}                |
|                                   |                                   |
| δy of F-CAM                       | δy of D-CAM                       |
+-----------------------------------+-----------------------------------+
| ![](media/image37.                | ![](media/image38.                |
| wmf){width="2.9166666666666665in" | wmf){width="2.9166666666666665in" |
| height="2.1875in"}                | height="2.1875in"}                |
|                                   |                                   |
| δy of P-CAM                       | δy of R-CAM                       |
+-----------------------------------+-----------------------------------+

Fig. 8 δy of four cameras

###### Intrinsic and extrinsic parameters {#intrinsic-and-extrinsic-parameters .unnumbered}

The intrinsic and extrinsic parameters for different cameras were
calibrated and are listed in the following table.

Table 9 Intrinsic and extrinsic parameters

<table style="width:100%;">
<colgroup>
<col style="width: 9%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
</colgroup>
<tbody>
<tr class="odd">
<td>Parameters</td>
<td colspan="3">F-CAM</td>
<td colspan="3">D-CAM</td>
<td colspan="3">P-CAM</td>
<td colspan="3">R-CAM</td>
</tr>
<tr class="even">
<td rowspan="4">R<sup>T</sup></td>
<td>R<sub>1</sub></td>
<td>R<sub>2</sub></td>
<td>R<sub>3</sub></td>
<td>R<sub>1</sub></td>
<td>R<sub>2</sub></td>
<td>R<sub>3</sub></td>
<td>R<sub>1</sub></td>
<td>R<sub>2</sub></td>
<td>R<sub>3</sub></td>
<td>R<sub>1</sub></td>
<td>R<sub>2</sub></td>
<td>R<sub>3</sub></td>
</tr>
<tr class="odd">
<td colspan="3" rowspan="3"><p>-1.0000 -0.0042 -0.0035</p>
<p>-0.0011 -0.9743 -0.2252</p>
<p>-0.0038 -0.2252 0.9743</p></td>
<td colspan="3" rowspan="3"><p>-0.7018 -0.1878 0.6877</p>
<p>0.0535 -0.9763 -0.2092</p>
<p>0.7103 -0.1080 0.6952</p></td>
<td colspan="3" rowspan="3"><p>-0.7390 -0.3102 -0.5965</p>
<p>0.6001 -0.7109 -0.3714</p>
<p>-0.3063 -0.6312 0.7115</p></td>
<td colspan="3" rowspan="3"><p>0.9921 -0.0326 0.1207</p>
<p>-0.0037 -0.9678 -0.2518</p>
<p>0.1257 0.2496 -0.9602</p></td>
</tr>
<tr class="even">
</tr>
<tr class="odd">
</tr>
<tr class="even">
<td>T<sup>T</sup> (m)</td>
<td colspan="3">-0.0658 1.6280 0.5324</td>
<td colspan="3">0.3428 1.0512 0.0723</td>
<td colspan="3">-1.1015 1.0498 0.5364</td>
<td colspan="3">-0.5286 1.4410 0.4298</td>
</tr>
<tr class="odd">
<td>(i0,j0)</td>
<td colspan="3">359.79, 222.63</td>
<td colspan="3">348.61, 226.08</td>
<td colspan="3">366.81, 216.45</td>
<td colspan="3">361.05, 206.93</td>
</tr>
<tr class="even">
<td>(f/w<sub>x</sub> ,f/ w<sub>y</sub>)<sup>1</sup></td>
<td colspan="3">860.83, 790.62</td>
<td colspan="3">461.00, 419.96</td>
<td colspan="3">438.66, 403.40</td>
<td colspan="3">841.70, 771.48</td>
</tr>
<tr class="odd">
<td>(p1,p2,k1)/f</td>
<td colspan="3">-0.0146 -0.0056 -0.1434</td>
<td colspan="3">-0.0064 -0.0044 -0.2342</td>
<td colspan="3">-0.0006 -0.0048 -0.2447</td>
<td colspan="3">-0.0108 -0.0055 -0.1486</td>
</tr>
</tbody>
</table>

1.  *The imaging element size parameter*
    ![](media/image23.wmf){width="0.4861111111111111in"
    height="0.2638888888888889in"}*can not be determined in the
    calibration procedure. These parameters can be found in camera
    manufacturer's specifications. The cameras mounted on bus No.1 are
    from ELMO. The camera head model is MH42H. The effective image area
    is 6.54mmx4.89mm. Effective image pixels are 768 x 494. By simple
    calculation, the size parameters are:*

###### Derived parameter verification {#derived-parameter-verification .unnumbered}

Some parameters can be derived from the calibrated parameters. Location
of the cameras can be derived by \[5\]:

![](media/image39.wmf){width="0.8888888888888888in"
height="0.7777777777777778in"}.

Focus length of the cameras can be calculated by simply multiplying
![](media/image40.wmf){width="0.44375in"
height="0.25in"}with![](media/image41.wmf){width="0.2222222222222222in"
height="0.25in"} or multiplying ![](media/image42.wmf){width="0.44375in"
height="0.2638888888888889in"}with![](media/image43.wmf){width="0.2222222222222222in"
height="0.2638888888888889in"}. Angles of the cameras can be calculated
from the rotation matrix R:

Tilting angle = -![](media/image44.wmf){width="0.7222222222222222in"
height="0.25in"};

Azimuth angle = -![](media/image45.wmf){width="1.0in" height="0.25in"}

Image rotation = ![](media/image46.wmf){width="0.7222222222222222in"
height="0.2361111111111111in"}

These derived parameters are listed in the following table.

Table 10 Derived parameters

  ----------------- ---------- ------------ ---------- ------------ ---------- ------------ ---------- ------------
                    F-CAM                   D-CAM                   P-CAM                   R-CAM      

                    Measured   Calculated   Measured   Calculated   Measured   Calculated   Measured   Calculated

  Location X (mm)   -69        -57          396        388          -109       -168         500        523

  Location Y (mm)   1653       1706         991        1023         1563       1607         1500       1501

  Location Z (mm)   -61        -152         -80        -180         -95        -56          140        111

  Focus fx (mm)     7.5        7.32         4.0        3.92         4.0        3.73         7.5        7.15

  Focus fy (mm)     7.5        7.83         4.0        4.16         4.0        3.99         7.5        7.64

  Tilting Ang (Deg) 13         13.01        14         12.1         25         21.8         16         14.6

  Azimuth Ang (Deg) N.A.       0.20         N.A.       -44.7        N.A.       40.0         N.A.       7.2

  Image Rotation    N.A.       -0.06        N.A.       3.06         N.A.       31.0         N.A.       -0.21
  Ang (Deg)                                                                                            
  ----------------- ---------- ------------ ---------- ------------ ---------- ------------ ---------- ------------

### ***System alignment*** {#system-alignment .unnumbered}

The purpose of system alignment is to determine the inter-relationship
of multiple sensors in the system. Three sensors, LIDAR, P-RADAR and
D-RADAR, are considered. Thirteen locations were marked on the ground in
front of the bus. A microwave reflector and a laser reflector were used
as targets for the sensors. A person moving from location to location in
the order of the numbers illustrated in Fig. 81 held both reflectors.
When the person moved to one location, he stayed there for about six
seconds, with the microwave reflector swinging forth and back to
simulate a moving target. Data was collected in the on-bus computer.
This is plotted in Fig. 82 thru Fig. 84.

![](media/image47.wmf){width="5.692361111111111in" height="2.33125in"}

Fig. 9 Object locations for system alignment

![](media/image48.wmf){width="5.823611111111111in"
height="2.995138888888889in"}

Fig. 10 PRADAR data for system alignment

![](media/image49.wmf){width="5.823611111111111in"
height="2.932638888888889in"}

Fig. 11 DRADAR data for system alignment

![](media/image50.wmf){width="5.531944444444444in"
height="3.120138888888889in"}

Fig. 12 LIDAR data for system alignment

The target parameters on the marked locations were extracted from the
data and transformed to the bus coordinate system (FCS). Deviations are
then calculated with the assumption that the marked locations are
precise. The deviations are listed in Table 42 and plotted in Fig. 13.
The average deviation of both distance and lateral position is less than
1m. This indicates the sensors are aligned well.

![](media/image51.wmf){width="5.357638888888889in" height="3.7375in"}

Fig. 13 Object locations reported by sensors

Table 11 Object locations reported by sensors

<table>
<colgroup>
<col style="width: 9%" />
<col style="width: 9%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 0%" />
<col style="width: 7%" />
<col style="width: 7%" />
</colgroup>
<tbody>
<tr class="odd">
<td rowspan="3"><p><strong>Locat.</strong></p>
<p><strong>#</strong></p></td>
<td colspan="4"><strong>LIDAR</strong></td>
<td colspan="4"><strong>Passenger Side Radar</strong></td>
<td colspan="5"><strong>Driver Side Radar</strong></td>
</tr>
<tr class="even">
<td colspan="2"><strong>Report</strong></td>
<td colspan="2"><strong>System (m)</strong></td>
<td colspan="2"><strong>Report</strong></td>
<td colspan="2"><strong>System (m)</strong></td>
<td colspan="2"><strong>Report</strong></td>
<td colspan="3"><strong>System (m)</strong></td>
</tr>
<tr class="odd">
<td>R(H/L)<sup>1</sup></td>
<td>L<sup>2</sup></td>
<td>Ds<sup>5</sup></td>
<td>Ls<sup>5</sup></td>
<td>R<sup>3</sup></td>
<td>α<sup>4</sup></td>
<td>Ds<sup>5</sup></td>
<td>Ls<sup>5</sup></td>
<td>R<sup>3</sup></td>
<td>α<sup>4</sup></td>
<td colspan="2">Ds<sup>5</sup></td>
<td>Ls<sup>5</sup></td>
</tr>
<tr class="even">
<td>1</td>
<td>8/00</td>
<td>-9</td>
<td><strong>10.32</strong></td>
<td><strong>0.23</strong></td>
<td>340</td>
<td>-19</td>
<td><strong>10.43</strong></td>
<td><strong>-0.66</strong></td>
<td colspan="5">Missed</td>
</tr>
<tr class="odd">
<td>2</td>
<td>16/29</td>
<td>-9</td>
<td><strong>20.85</strong></td>
<td><strong>0.40</strong></td>
<td>690</td>
<td>-11</td>
<td><strong>21.10</strong></td>
<td><strong>-0.59</strong></td>
<td>680</td>
<td>30</td>
<td colspan="2"><strong>20.76</strong></td>
<td><strong>-0.26</strong></td>
</tr>
<tr class="even">
<td>3</td>
<td colspan="4">Missed</td>
<td colspan="4">Missed</td>
<td colspan="5">Missed</td>
</tr>
<tr class="odd">
<td>4</td>
<td>16/30</td>
<td>23</td>
<td><strong>20.86</strong></td>
<td><strong>-2.80</strong></td>
<td colspan="4">Missed</td>
<td colspan="5">Missed</td>
</tr>
<tr class="even">
<td>5</td>
<td>24/00</td>
<td>-8</td>
<td><strong>30.80</strong></td>
<td><strong>0.46</strong></td>
<td>910</td>
<td>-5</td>
<td><strong>27.81</strong></td>
<td><strong>-0.77</strong></td>
<td>930</td>
<td>18</td>
<td colspan="2"><strong>28.4</strong></td>
<td><strong>-0.04</strong></td>
</tr>
<tr class="odd">
<td>6</td>
<td>23/33</td>
<td>-58</td>
<td><strong>29.85</strong></td>
<td><strong>5.46</strong></td>
<td colspan="4">Missed</td>
<td colspan="5">Missed</td>
</tr>
<tr class="even">
<td>7</td>
<td>24/29</td>
<td>42</td>
<td><strong>31.09</strong></td>
<td><strong>-4.54</strong></td>
<td>860</td>
<td>45</td>
<td><strong>26.17</strong></td>
<td><strong>-3.41</strong></td>
<td colspan="5">Missed</td>
</tr>
<tr class="odd">
<td>8</td>
<td>31/88</td>
<td>-7</td>
<td><strong>40.56</strong></td>
<td><strong>0.53</strong></td>
<td>1253</td>
<td>-3</td>
<td><strong>38.26</strong></td>
<td><strong>-0.82</strong></td>
<td>1290</td>
<td>12</td>
<td colspan="2"><strong>39.38</strong></td>
<td><strong>0.04</strong></td>
</tr>
<tr class="even">
<td>9</td>
<td>30/90</td>
<td>-57</td>
<td><strong>39.38</strong></td>
<td><strong>5.53</strong></td>
<td colspan="4">Missed</td>
<td>1442</td>
<td>-37</td>
<td colspan="2"><strong>43.90</strong></td>
<td><strong>4.23</strong></td>
</tr>
<tr class="odd">
<td>10</td>
<td>32/40</td>
<td>43</td>
<td><strong>41.44</strong></td>
<td><strong>-4.47</strong></td>
<td>1375</td>
<td>41</td>
<td><strong>41.84</strong></td>
<td><strong>-4.48</strong></td>
<td colspan="5">Missed</td>
</tr>
<tr class="even">
<td>11</td>
<td>39/30</td>
<td>-7</td>
<td><strong>50.22</strong></td>
<td><strong>0.7</strong></td>
<td>1680</td>
<td>-7</td>
<td><strong>51.27</strong></td>
<td><strong>-0.33</strong></td>
<td>1680</td>
<td>22</td>
<td colspan="2"><strong>51.23</strong></td>
<td><strong>-1.27</strong></td>
</tr>
<tr class="odd">
<td>12</td>
<td>38/80</td>
<td>-57</td>
<td><strong>49.44</strong></td>
<td><strong>5.7</strong></td>
<td colspan="4">Missed</td>
<td>1628</td>
<td>-38</td>
<td colspan="2"><strong>49.55</strong></td>
<td><strong>4.75</strong></td>
</tr>
<tr class="even">
<td>13</td>
<td>40/20</td>
<td>43</td>
<td><strong>51.4</strong></td>
<td><strong>-4.3</strong></td>
<td>1752</td>
<td>27</td>
<td><strong>53.39</strong></td>
<td><strong>-3.53</strong></td>
<td colspan="5">Missed</td>
</tr>
<tr class="odd">
<td colspan="2">Deviation Range</td>
<td>-</td>
<td><p><strong>-0.62</strong></p>
<p><strong>1.44</strong></p></td>
<td><p><strong>0.23</strong></p>
<p><strong>0.7</strong></p></td>
<td>-</td>
<td>-</td>
<td><p><strong>-3.83</strong></p>
<p><strong>3.39</strong></p></td>
<td><p><strong>-0.77</strong></p>
<p><strong>1.59</strong></p></td>
<td>-</td>
<td colspan="2">-</td>
<td><p><strong>-1.60</strong></p>
<p><strong>3.90</strong></p></td>
<td><p><strong>-1.27</strong></p>
<p><strong>0.04</strong></p></td>
</tr>
<tr class="even">
<td colspan="2">Average Deviation</td>
<td>-</td>
<td><strong>0.52</strong></td>
<td><strong>0.49</strong></td>
<td>-</td>
<td>-</td>
<td><strong>-0.09</strong></td>
<td><strong>0.05</strong></td>
<td>-</td>
<td colspan="2">-</td>
<td><strong>0.54</strong></td>
<td><strong>-0.43</strong></td>
</tr>
</tbody>
</table>

1.  *Range. 'H/L' are two bytes of Lidar report. The LSB of H-byte is
    1.28m and that of L-byte is 0.01m.*

2.  *Lateral position.*

3.  *Radar range is an integer, multiples of 0.1ft.*

4.  *Azimuth angle. Radar azimuth angle is an integer, multiples of
    0.002rad.*

5.  *Distance and lateral position in bus coordinate system.*

### ***Host vehicle parameter*** {#host-vehicle-parameter .unnumbered}

#### Offset {#offset .unnumbered}

The following host vehicle (bus) parameters are biased in the collected
data: steering angle, acceleration, brake pressure and wheel speed. The
biased values were measured when the bus was stationary and are listed
in the following Table.

Table 12 Host vehicle parameter biased values

  ----------------------------------------- ------------------------------
  **Parameter**                             **Biased Value**

  Steering Angle                            7.36

  X Acceleration                            2.40

  Y Acceleration                            2.45

  Z Acceleration                            2.45

  Brake Pressure                            1.02

  Wheel Speed                               0.038574
  ----------------------------------------- ------------------------------

Sensitivity

##### Steering angle sensor {#steering-angle-sensor .unnumbered}

The bus hand-wheel was turned counterclockwise as far as it would go,
held for five seconds, then turned clockwise step by step. For each step
the hand-wheel was rotated 120 degrees and held for five seconds (the
last turn was less than 120 degrees). The steering angle sensor outputs
when the hand-wheel was held are listed below:

8.715820 (anticlockwise end)

8.525391

8.374023

8.198242

8.012695

7.822266

7.631836

7.441406

7.255859

7.070312

6.894531

6.723633

6.562500

6.406250

6.254883

6.201172 (after the last turn)

Average sensitivity factor is 1.5 mV/degree. Average angle-to-voltage
ratio is 687.6148 degrees/V. The Steering ratio is 20.42:1 (for every
degree of road wheel change requires 20.42 degrees of handwheel input).
The wheel base is 279 inches.

##### Accelerometer {#accelerometer .unnumbered}

The accelerometer sensitivity is given by Summit Instruments as (unit:
mV/g):

Table 13 Accelerometer sensitivity

  ----------------------- ----------------------- -----------------------
                          To X Acceleration       To Y Acceleration

  X Sensitivity           1302.31                 8.76

  Y Sensitivity           -13.07                  1299.00

  Z Sensitivity           -3.25                   2.97
  ----------------------- ----------------------- -----------------------

The accelerometer was not calibrated on the bus.

##### Brake pressure {#brake-pressure .unnumbered}

The brake pressure transducer output is proportional to the pressure.
The sensitivity factor is 50mV/psi. The pressure range is 0-100psi. The
corresponding output range is 1-6V.

## Data storage  {#data-storage .Style-Heading-2-+-Justified-Left:--0\"-First-line:--0\"-Before:--1...}

This project has generated large amounts of data. Currently there are
over 200 gigabytes of video and sensor data. The data was initially
stored on one computer with three large hard drives but soon the data
storage reached its maximum capacity. A new storage solution was
therefore developed. This new storage method is built using a RAID. It
currently has 800 gigabytes of storage capacity which will allow this
project to collect full data from three buses for one year. The RAID can
be expanded to 1.5 terabytes if necessary. Later in the project we
expect to perform more selective data collection which will reduce the
rate of data collection. This will be done by only collecting data when
the warning algorithm has given an alert. The new storage system is
connected through the internet to allow users obtain data online. The
RAID-based storage system has proven to be the most convenient and
economical solution to our data storage needs.

## References {#references .Style-Heading-2-+-Justified-Left:--0\"-First-line:--0\"-Before:--1...}

1.  Denso Lidar documents, Denso Inc.

2.  Lenz, R.K.; Tsai, R.Y. Techniques for calibration of the scale
    factor and image center for high accuracy 3-D machine vision
    metrology, Pattern Analysis and Machine Intelligence, IEEE
    Transactions on , Volume: 10 Issue: 5 , Sept. 1988, Page(s): 713
    -720.

3.  Bacakoglu, H.; Kamel, M.S. A three-step camera calibration method.
    IEEE Transactions on Instrumentation and Measurement, vol.46,
    (no.5), IEEE, Oct. 1997. p.1165-72.

4.  Weng, J.; Cohen, P.; Herniou, M. Camera calibration with distortion
    models and accuracy evaluation. IEEE Transactions on Pattern
    Analysis and Machine Intelligence, vol.14, (no.10), Oct. 1992.
    p.965-80.

5.  Wu, L.D., Computer Vision, Fudan University, China, Dec. 1993.

  ---------------------- ------------------------------------------------
  Appendix VI:           Suggestions on Other Display Modalities

  ---------------------- ------------------------------------------------

Table 14 Audible warnings feedback from operators and trainers

  -------------------- -----------------------------------------------------
  Requirement from     Requirement
  Operators/Trainers   

  T                    Suggested an earbud since it would provide a private
                       audio warning, but recognized that operators would
                       probably not be too keen on wearing them.

  T                    Sound was perceived to be a more effective option
                       than vision as a knowledgeable operator would not
                       have to look at anything to detect the warning.

  T                    Operators are trained to look down when an audible
                       alarm trips as they often signal a mechanical
                       problem. Instrument panel lights are used to identify
                       the problem.

  D                    Ambient sound levels within a bus can vary due to
                       passenger load.

  D                    Operators find some existing warnings very annoying,
                       especially when repeated false alarms occur. One
                       example frequently cited was the rear door buzzer.

  D                    Speakers placed behind the operator\'s head (e.g.,
                       one on each side for directional information) were
                       uniformly rejected. This location was perceived to be
                       too startling. Music was identified as the only
                       acceptable audio source from this location

  D                    One operator proposed a dash-mounted display similar
                       to an on-board radar screen for airplanes.

  D                    Head-Up Displays (HUDs) were voluntarily suggested.
                       Operators were aware that the cost would likely be
                       too great. For a detailed discussion of additional
                       problems with HUDs in transit buses see \[Error:
                       Reference source not found\].

  D                    Dash lights already flicker often during normal
                       driving (e.g., when braking, retarder activation,
                       etc.).

  D                    Operators with night runs indicated that there is
                       already too much illumination in the cab and were not
                       enthusiastic about additional light sources. The
                       ability to dim the illumination level or even shut
                       off visual warnings was requested. Redundant warnings
                       in other modalities (e.g., audible) were recommended
                       for night driving.

  DT                   Experienced operators often downplayed the value of
                       dash-mounted visual warnings as they rarely look at
                       their instrument cluster.
  -------------------- -----------------------------------------------------

  ----------------- -----------------------------------------------------
  D                 Audible warnings that change pitch as the danger
                    increases were suggested.

  D                 Chimes or other subtle, pleasant sounds were
                    suggested as ways to provide alerts (prior to
                    full-blown warnings).

  D                 Ramping up the volume or pitch was suggested as a way
                    to not startle the operator.

  D                 Concern over having passengers mimic the sound of any
                    warning
  ----------------- -----------------------------------------------------

Table 15 Tactile warnings feedback from operators and trainers

  -------------------- -----------------------------------------------------
  Requirement from     Requirement
  Operators/Trainers   

  DT                   Seat vibrations were roundly described as not
                       worthwhile. One operator commented, *\"After 8 hours
                       I don\'t have any idea what\'s going on down
                       there.\"*
  -------------------- -----------------------------------------------------

Table 16 Vehicle control feedback from operators and trainers

  -------------------- -----------------------------------------------------
  Requirement from     Requirement
  Operators/Trainers   

  D                    Operators voluntarily suggested longitudinal control
                       actions by the bus. The existing interlock was
                       subsequently mentioned as a potential method. The
                       interlock activates whenever the rear door is opened
                       by applying brake pressure to the two rear wheels.
                       This prevents the bus from rolling away while
                       passengers are loading. In the past, the interlock
                       would be triggered if the rear door was opened while
                       the bus was in motion. Maintenance has prevented the
                       rear door from opening while in motion due to
                       concerns over brake wear. Experienced operators
                       described the braking action as being smooth enough
                       to prevent falls, yet fast enough to bring the bus to
                       rest.
  -------------------- -----------------------------------------------------

## Audible component design

One of the more interesting operator suggestions was to use a
non-traditional auditory sound for the alert level (in this case a chime
or a clock tick). This level would be the point at which the system
indicates that there might be a target that could lead to a critical
threat. The use of a chime or some other semi-pleasant notification
earcon for this threshold is important, as this event will be somewhat
frequent. A comparable warning would be the soft thunderclap or
\"clink\" sound used by supermarkets to warn patrons in the produce
section of an upcoming water spray. The sound is unique enough for
patrons and employees to detect, yet is not obtrusive enough to annoy
those present.

For cases of true critical events (i.e., chances are high that a crash
will occur) a more salient and obtrusive earcon was recommended.
Furthermore, the warning should not be binary in nature. The volume
should ramp up as the threat level increases. In reality, the inclusion
of a volume knob will allow operators to have either earlier or later
perception, as the early ramping phase will be highly affected by the
knob setting.

Speaker positioning will be important, as it will be necessary to
provide a clear sound to the operator without being readily detectable
to the passengers. Obviously the trainer suggestion of ear buds would be
the easiest solution but the driving population would not accept these.
Speakers behind the operator\'s head are another logical solution, but
again, this was not popular with the operators. The remaining options
are in front of the operator as side mounted locations will be directed
towards passengers in the front seats and the sounds will not have good
spatial mapping to the forward threat \[1\]. Final speaker placement
will likely be done during the DVI installation process as the geometry
of the cab is complex.

## References {#references-1 .unnumbered}

######### Tan, A. K., & Lerner, N. (1996). Acoustic Localization of In-Vehicle Crash Avoidance Warnings as a Cue to Hazard Direction (DOT HS 808 534). Washington, DC: National Highway Traffic Safety Administration. {#tan-a.-k.-lerner-n.-1996.-acoustic-localization-of-in-vehicle-crash-avoidance-warnings-as-a-cue-to-hazard-direction-dot-hs-808-534.-washington-dc-national-highway-traffic-safety-administration. .Reference}

#########  {#section .Reference .unnumbered}

Appendix VII: FCWS Survey Questions

**Forward Collision Warning System (FCWS) Evaluation Survey Questions**

**SamTrans February 2002**

We would like to ask you some questions regarding your opinion of the
FCWS. We will not be recording your identity and this information will
not be associated with you or be used as a means of evaluating your
performance. We are only interested in evaluating the system.

Your participation is voluntary. You are free to refuse to take part.
You may refuse to answer any question and may stop taking part in the
study at any time. Whether or not you participate in this research will
have no bearing on you standing in your job.

**Background information:**

How long have you been driving buses?

**Probing Questions -- used as required:**

Did the system function the way that you thought it would?

> Please describe any instances where you felt that you should have
> received a warning but didn't?
>
> Please describe any instances where you received a warning and felt
> that you shouldn't have?

Do you like the system?

Did you find the system easy to use?

How long do you think you would need to become comfortable with the
system?

When did the system provide you with the most assistance?

Would you like to drive with the system the way it currently is?

If you could change/add one feature what would it be?

Questions/comments

Appendix VIII: FCWS Evaluation Questionnaire

**Forward Collision Warning System (FCWS) Evaluation Questionnaire**

**SamTrans April 2002**

We would like to ask you some questions regarding your opinion of the
FCWS. We will not be recording your identity and this information will
not be associated with you or be used as a means of evaluating your
performance. We are only interested in evaluating the system.

Your participation is voluntary. You are free to refuse to take part.
You may refuse to answer any question and may stop taking part in the
study at any time. Whether or not you participate in this research will
have no bearing on you standing in your job.

**Background information:**

> How long have you been driving buses? \_\_\_\_\_\_\_\_\_\_\_
>
> Approximately how many hours have you driven the bus with the FCWS
> on?\_\_\_\_\_\_\_\_\_
>
> Did you receive any training prior to using the
> FCWS?\_\_\_\_\_\_\_\_\_\_\_

**General Assessment:**

1.  Please describe the system and how it works the way that you would
    to another operator that has not yet seen or used the system.

\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_

For the following questions, please rate how well the system performs:

  --------------------------------- -------------------------------------
  How easy is the system to use     (not easy) 1 2 3 4 5 (very easy)
  overall?                          

  How much do you like the system   (not at all) 1 2 3 4 5 (a lot)
  overall?                          

  How well do you think the         (not at all) 1 2 3 4 5 (a lot)
  warnings conveyed a sense of      
  urgency?                          

  If you had more time with the     (no) 1 2 3 4 5 (yes)
  system, would you like it more?   

  Do you think that they system is  (not at all) 1 2 3 4 5 (extremely)
  beneficial in terms of increasing 
  your safety?                      

  How annoying was the system?      (not at all) 1 2 3 4 5 (extremely)

  How distracting was the system?   (not at all) 1 2 3 4 5 (extremely)
  --------------------------------- -------------------------------------

#  {#section-1 .unnumbered}

#  {#section-2 .unnumbered}

#  {#section-3 .unnumbered}

#  {#section-4 .unnumbered}

#  {#section-5 .unnumbered}

#  {#section-6 .unnumbered}