Final Report

####### 

####### 

####### **[Assessment of automated]{.smallcaps}**

######### **Data Collection Technologies**

**[for Calculation of]{.smallcaps}**

**[Commercial Motor Vehicle]{.smallcaps}**

**[Border Crossing Travel]{.smallcaps}**

**[Time Delay]{.smallcaps}**

To

Office of Freight Mgt. and Operations

Federal Highway Administration

U.S. Department of Transportation

Washington, DC 20590

![](media/image1.png)

 

April 2002

# 

# 

# 

## **VERSION 1.0**

## **Assessment of Automated Data Collection** 

## **Technologies for Calculation of Commercial Motor** 

## **Vehicle Border Crossing Travel Time Delay** 

**by**

**Battelle**

**505 King Avenue**

**Columbus, Ohio 43201**

**for**

**U.S. Department of Transportation**

**Washington D.C.**

**Contract No. DTFH61-96-C-00077**

**Task Order 7727**

**April 2002**

> **Disclaimer**

## 

## This report is a work prepared for the United States Government by Battelle. In no event shall either the United States Government or Battelle have any responsibility or liability for any consequences of any use, misuse, inability to use, or reliance on the information contained herein, nor does either warrant or otherwise represent in any way the accuracy, adequacy, efficacy, or applicability of the contents hereof.

This report is not intended as a definitive recommendation for a certain
'best" technology but rather as a guide for further detailed
investigation. Its intent is to portray the features of various
candidate technologies and relate them to the criteria that need to be
met by the application envisioned.

## **Table of Contents**

PREFACE iv

EXECUTIVE SUMMARY v

1.0 INTRODUCTION 1

1.  Purpose of the Report 1

2.  Organization of the Report 1

3.  Background 1

4.  Methodology 2

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2.  TECHNICAL APPROACH 2

    1.  Disadvantages of Manual Collection 2

    2.  Assumptions and Issues 5

    3.  Characteristics of the Border Crossings 6

    4.  Where Would Vehicle Sensing Technologies Be Located? 6

2.5 Overview of Vehicle Sensing Technologies 8

2.6 Candidate Sensing Technologies 9

> 2.6.1 Automatic Vehicle Identification (AVI) Laser 10

2.6.2 AVI Radio Frequency (RF) 10

#####  RF Tags 11

#####  RF Smart Tags 11 

#####  Smart Cards with RF Transponders 11 

##### 2.6.3 AVI Infrared (IR) 12

#####  IR Tags 12 IR Tags 

#####  Smart cards with IR Transponders 12 

> 2.6.4 Enhanced Common Inductive Loop 12
>
> 2.6.5 Signature Inductive Sensors (Enhanced Loop-Based Traffic
>
> Surveillance) 14
>
> 2.6.6 Mobile Phone Locating 14
>
> 2.6.7 License Plate Readers 16
>
> 2.6.8 Vehicle Matching 18

3.  OTHER CONSIDERATIONS 18

    1.  Cost 18

    2.  Maturity of the technologies for deployment 19

    3.  Site security/vandalism 19

    4.  Privacy 19

    5.  Portability 20

    6.  Hourly count data 20

    7.  Developments in response to 9/11 21

4.  TECHNOLOGY TRADE-OFF MATRIX 21

5.  CONCLUSIONS 22

6.  REFERENCES 23

# APPENDIX A: Trade-Off Comparison of Automated Technologies 25

###### List of Tables

# Table 1 Table 1. Comparison of Vehicle Sensing Technologies 9

# Table 2 Summary Matrix of Candidate Sensing Technologies 22

###### List of Figures

Figure 1. Data Collectors Have To Make Safety the Top Priority 3

Figure 2. The Head of a Queue Can Be Far Away from the Border Crossing 4

Figure 3. Primary on the Mexican Side of the Zaragoza Bridge (El
Paso-Juarez) 7

Figure 4. Primary on the U.S. Side of the Zaragoza Bridge (El
Paso-Juarez) 7

Figure 5. Some of the Border Crossings Have Large, Imposing Bridges 8

Figure 6. Discharge from Primary Can Be Congested 8

Figure 7. License Plate Reader at the Zaragoza Bridge, El Paso
(Automobile Side) 17

# **PREFACE**

# 

# 

# Battelle is performing an ITS Program Assessment Support (IPAS) contract for the Federal Highway Administration Office of Freight Management and Operations, under the task "Expansion of Initial Border Measurement Activity -- Analysis and Expansion of Sites in 2001." Specifically, Battelle's task under this contract is "Evaluation of Travel Time Methods to Support Mobility Performance Monitoring," contract DTFH61-96-C-00077. Broadly, the task is to collect and compile data on travel time delays experienced by CMVs (commercial motor vehicles, i.e., trucks) crossing the U.S. border to, and from, Canada and Mexico.

# 

# Battelle's contract involves technical support for:

# (1) conducting second on-site visits to several international border crossing sites observed in an FY 2000 review of commercial motor vehicle (CMV) travel time, for the purpose of additional collection and analysis of CMV travel data;

# nomination of 3 additional crossing sites at Canadian and Mexican borders for evaluation of their CMV travel times;

# (3) collection and analysis of FY 2001 CMV travel time data at all 7 crossings; and

# (4) incorporation into final analysis of separately collected data at 2 additional international sites that, in 2001, will be concurrently assessing the application of automated border collection and analysis software. 

# 

As part of item (4) above, this report evaluates the potential for
application of automated monitoring technologies at the sites reviewed
in FY 2001 and early FY 2002. These are specific technologies that have
promise for automating the collection and determination of CMV (truck)
travel times across the U.S. border with Canada and Mexico.

EXECUTIVE SUMMARY

## This report describes an evaluation of the benefits and overall potential of technologies that may be used to collect truck travel time data in place of specialized onsite data collectors at border crossings between the U.S. and its neighbors - Mexico and Canada. The report identifies and examines various technologies whose characteristics make them potentially suited to collecting this type of data. In addition, the report also examines their maturity for deployment as well as certain other characteristics that affect their suitability for the intended purpose. The technologies are presented in terms of basic functionality, not detailed specifications. Therefore, the results are intended only as a guide.

The author has chosen to include the assessment of certain technologies
that are in a development or prototype stage and thus not yet
commercially available, but which have potential for automating the
travel time process when developed. Some of the other technologies
identified are currently used for other applications but should be
capable of being adapted to perform in a manner that should achieve the
necessary criteria. This technology assessment focuses principally on
sensing technologies, not on the software needed to translate raw data
into useful compilations.

No one sensing technology is a clear favorite; each candidate has to be
weighed in terms of functionality, cost, concept and length of
operations, maturity and availability as well as more mundane
considerations like susceptibility to environmental degradation and
vandalism.

Any follow-on studies should not be done in isolation from current
homeland security concepts being discussed for border crossings. There
will probably be very few installations of any of these technologies for
the sole purpose of data collection. The technologies discussed in this
report should be leveraged with those national security efforts, other
federal inspection and trade agency initiatives and local operating
efficiency enhancements in a mutually beneficial arrangement.

## 

## 

# 

#  

1.0 INTRODUCTION

1.  Purpose of the Report

This report is submitted to assess the potential of certain technologies
to determine commercial vehicle travel time at border crossings by
automated means.

**1.2 Organization of the Report**

The technology assessment begins by describing the current method of
collecting truck travel time data and calculating delay. Next there is a
discussion of the assumptions that underlie the deployment of an
automated system. Also discussed are the types of functions that a
vehicle sensing technology would have to possess in order to perform
effectively in an automated system that replaces some or all of the
persons who currently man the data collector functions at a border
crossing. This involves examining all of the current vehicle sensing
technologies and their features in certain key areas. Then the sensing
technologies that possess some of the desired traits will be examined in
greater depth. Their basic function as well as advantages and
disadvantages will be discussed.

**1.3 Background**

The FHWA acknowledges, **"**Our international border crossings are
important links in the chain of freight commerce. They are also
potential obstacles to efficient movement, imposing delays in response
to a number of competing, but necessary Federal and State agency
activities, such as immigration status verification, vehicle safety
assessments, cargo assessments, drug interdiction, and toll payments.

"To ensure that [transportation-related]{.underline} activities can be
made less burdensome and facilitate the efficient and expeditious
movement of cargoes across our borders, the Office of Freight Management
and Operations ([HOFM]{.underline}) began, in FY 2000, to collect
empirical information about the actual movement of commercial vehicles,
traveling from exporting to importing country, at designated crossings
along the Mexican and Canadian borders. HOFM's purpose in FY 2000 was to
establish a "baseline" of vehicle travel times at these locations."

Three border crossings had truck travel time data collected in the FY
2000 effort:

-   Otay Mesa, California

-   World Trade Bridge, Laredo, Texas

-   Calais, Maine

Seven border crossings had truck travel time data collected in the FY
2001 effort:

-   Ambassador Bridge, Michigan

-   Bluewater Bridge, Michigan

-   Peace Bridge, New York

-   Zaragoza Bridge, El Paso, Texas

-   Blaine, Washington

-   Otay Mesa, California\*

-   World Trade Bridge, Laredo, Texas\*

\*Otay Mesa and Laredo received data collection on both the FY 2000 and
FY 2001 activity.

**1.4 Methodology**

"Travel time per truck trip" is the measurement chosen to monitor travel
time and delay at the border sites. This encompasses the time taken by
an individual commercial vehicle from:

-   The initial queuing point in the exporting country,

-   Through the exporting country's checkpoint, and

-   Up to and through the first inspection point in the importing
    country.

-   Travel in both directions is assessed.

Measurements are taken: (1) at various times during the individual
workday and (2) during one or more seasons of the year. "Travel delay"
as a measurement is based on an initial determination, at an individual
site, of the time required for *relatively low volumes* of traffic to
proceed through the location. Additional measurements are then taken
throughout the business day, with special attention to times when
significant delays may occur. Data collected at these times are compared
to the initial, low volume of activity at the site, and conclusions
drawn.

1.  TECHNICAL APPROACH

2.1 Disadvantages of Manual Collection

The process of getting data collectors onsite and ready to go at a
border crossing is detailed and expensive. The collection itself can be
physically challenging. There are a number of areas in which automating
the process of data collection would offset current disadvantages.
Permanent or semi-permanent vehicle sensing technologies, capable of
operating in inclement weather, would be an attractive alternative to
the current labor-intensive process.

# [Sovereignty Issues]{.underline}

While Canada and Mexico are friendly nations, getting permission to
operate on their soil is not trivial, even with NAFTA. In all cases,
data collectors must have the absolute approval of Customs and
Immigration. That approval must include provision for being in that
nation as well as on the premises of their facilities. Formal,
time-consuming paperwork is often required. Any equipment installed in
Mexico or Canada would need written approval also, but its continued
operation would generally be on a non-recurring basis. Conversely,
on-site personnel typically have to have written permission or passes
from one or more agencies for each visit.

[Other Approvals]{.underline}

Crossings that have bridges may have private authorities, (such as
Ambassador Bridge at Detroit-Windsor), who own and operate the bridges
and whose approval is required while on their property. Toll operations
may be conducted by a national agency (as in Mexico), a city (as in
Laredo and El Paso), or an authority (as Ambassador Bridge). Their
approval is also required.

A host of additional approvals may be needed, including national or
state police, the General Services Administration (GSA) or its
equivalent across the border, local municipalities, local law
enforcement agencies, and consulates. Even with close communications,
data collection can easily get disrupted if knowledge of the agreed
arrangements hasn't reached all the right people in Customs,
Immigration, GSA or other on-site organizations. Some of these agencies
are large and it is important to ensure that every key person knows what
has been orchestrated.

[Logistics]{.underline}

In the majority of cases, data collectors have to travel an appreciable
distance to reach the site. That involves airfare, rental cars, lodging
and meals, labor, shipment of equipment, and sometimes out-of-country
auto insurance.

# [Safety]{.underline}

While this has not been a problem to date, there is no question that
operating in the vicinity of a stream of tractor-trailers whose drivers
are on tight deadlines requires collectors to be constantly aware of
their surroundings. A secondary issue is personal security. While data
collectors are generally in the vicinity of Customs operations, some may
have to venture to remote locations to stay ahead of a queue. This
situation can introduce new and unexpected traffic conditions. Or the
collector may find that the area does not appear to be in a particularly
safe neighborhood.

![](media/image2.jpeg){width="4.444444444444445in" height="2.80625in"}

**Figure 1. Data Collectors Have To Make Safety the Top Priority**

## 

## Weather

Temperatures along the Mexican border can easily top 100 degrees F. The
Canadian border can be hot as well, but rain -- particularly in
conjunction with cool temperatures -- can be challenging to the data
collector on the Canadian border. Of course, the Canadian crossings have
very cold temperatures during the winter months, but ice and snow would
affect many of the sensing technologies as well. Some of the collection
points experience high winds, and the data collectors may be exposed to
wind-driven grit generated by passing trucks. In fact, data collectors
in El Paso experienced dust storms at the Zaragoza Bridge crossing at El
Paso-Juarez during the 2001 truck travel study, at which time visibility
dropped rapidly. The effectiveness of sensing technologies can also be
reduced by weather, particularly fog, ice, and snow.

## Limited collection times

Data collectors must arrive at pre-determined times. The process of
scheduling those times must take into consideration national holidays on
both sides of the border. It must identify the periods that are most
conducive to actual collection of limited data. It must ensure that all
necessary approvals have been secured and word is out. Said another way,
there is pressure to ensure that quite a number of "moving pieces" come
together as planned so as to maximize the results possible during this
limited period. Any disruptions at this point, whatever their nature,
must be responded to aggressively.

#### 

## 

## ![](media/image3.jpeg){width="4.448611111111111in" height="3.3333333333333335in"}

## 

## **Figure 2. The Head of a Queue Can Be Far Away from the Border Crossing** 

## 

2.2 Assumptions and Issues

The essential function that any candidate sensing technology must
possess is the ability to collect data that allows measurement of truck
travel time and, consequently, delay. A number of technologies exist --
or soon will -- that can use a variety of approaches to accomplish that
same objective. However, there is a key challenge that confronts most of
the technologies that could potentially be used in the methodology. That
challenge is the need to have paired upstream and downstream
collectors - in the same traffic flow direction - located in different
countries. For the technologies that require onsite infrastructure to
accomplish that, sensing technologies will need to be in Canada or
Mexico in order to yield the paired data needed for matching. There is
only one technology type that would not require such infrastructure:
mobile phone locating, discussed in section 2.6.3.

Two important features that a successful sensing technology used for
this application must possess are the ability to (1) identify a specific
truck with a high degree of accuracy (i.e., 75% or greater), and (2)
record an individual truck with a high degree of geolocation accuracy.
That accuracy is assured with the technologies that have sensing
technologies situated at specific locations, but it is currently more
difficult to obtain with mobile phone locating.

It is not necessary that a sensing technology be able to capture every
vehicle for the purposes of travel time data collection. It may,
however, be an important requirement for inspection, tolling or other
cooperative uses. That is not practical with the current manual data
collection techniques, nor is there any compelling argument for an
automated system to capture 100 percent of the vehicles especially if
doing so results in higher costs. Total capture would be a useful
feature but not essential.

This might mean that sensor hardware could be mounted to read vehicles
in one of two or more lanes, assuming that there is no characteristic of
the facility's geographic layout that results in any appreciable
difference between the lanes. However, a collateral feature that is
desirable is the ability of the sensing technology to yield the hourly
crossing data, which has been difficult to get for both directions of
travel at some border crossings.

If a sensing technology requires infrastructure, then ideally the
sensing technologies will be mounted in similar -- or comparable -
configurations on both sides of a border crossing, for consistency.
Obviously, any such arrangement will have to be worked out with Mexico
or Canada. It is not often that the U.S. government purchases and
arranges installation of hardware across the border, although that has
reportedly been done.

Undoubtedly, there could be sensitivity to that issue unless it was
clear that it is expressly for traffic measurement or if the technology
is part of an operations improvement program for inspection and other
purposes. There might be many benefits that accrue to Mexican or
Canadian Customs, such as providing hourly counts, communicating trade
information or toll charges. The USDOT data needs can be integrated into
the information being communicated.

The license plate readers and vehicle matching technologies are sensing
technologies that require infrastructure and have portable options.
However, these portable options are quite expensive, costing tens of
thousands of dollars per lane, and these platforms may have problems
with vandalism if remotely located. It is difficult to align the
portable license plate readers in a manner that equals the effectiveness
of a hard-mounted reader.

2.3 Characteristics of the Border Crossings

Traffic flow measurements at the border crossings vary as a result of
season, day, time of day, number of booths manned by Customs personnel,
and additional security measures in effect (particularly after 9/11).
When there is no congestion at primary or upstream of it, then the flow
rate (trucks per hour) is equal to the existing demand (the amount of
traffic volume that results at a facility under some set of travel
conditions). This situation typically occurs when a crossing opens after
being closed for a night or before any traffic starts to build up. It is
used in the calculation for "travel time with no delay." If a queue
exists at the border crossing, then the measured flow rate reflects the
downstream bottleneck capacity; thus, actual measured flow rates would
be less than the demand. Delay is measured in terms of flow rate and
travel time in excess of the free-flow value.

2.4 Where Would Sensors Be Located?

For a technology that requires on-site infrastructure to replace data
collectors, two sensing technologies will be needed for each direction
of flow. The first sensor needs to be located in the exporting country
upstream from the entry point into the Customs facility, generally just
beyond the point to which queues ordinarily extend. Ideally, this would
be in a location that all inbound trucks must pass (in other words,
there are no other routes that could feed trucks into the queue
downstream from this point).

The second sensor needs to be a short distance downstream from primary
(in the importing country). Currently, downstream data collectors are
stationed within approximately 180 feet from the booths at the primary
checkpoint. The sensing technologies could perhaps be located where
trucks leaving from the bank of (up to ten) primary booths could be
funneled into fewer lanes, for technical considerations or reasons of
economy.

![](media/image4.jpeg){width="4.448611111111111in"
height="3.3333333333333335in"}

**Figure 3. Primary on the Mexican Side of the Zaragoza Bridge (El
Paso-Juarez)**

![](media/image5.jpeg){width="4.448611111111111in"
height="2.876388888888889in"}

**Figure 4. Primary on the U.S. Side of the Zaragoza Bridge (El
Paso-Juarez)**

Any radio frequency (RF) communications that are short-range or line-of
sight would not work well at some locations, particularly the ones at
which there are long bridges or a lot of steel mass (see figures 5 and
6).

![](media/image6.jpeg){width="4.444444444444445in" height="2.30625in"}

**Figure 5. Some of the Border Crossings Have Large, Imposing Bridges**

**(Shown: the Ambassador Bridge, Detroit-Windsor)**

![](media/image7.jpeg){width="4.444444444444445in"
height="3.3333333333333335in"}

**Figure 6. Discharge from Primary Can Be Congested**

**(Shown: Canadian side of Ambassador Bridge, Detroit-Windsor)**

**2.5 Overview of Vehicle Sensing Technologies**

Table 1 lists vehicle sensing technology types and examines a number of
characteristics that would factor into their individual suitability for
the intended purpose of travel time calculation. The top-level
characteristics of each are then discussed.

2.6 Candidate Sensing Technologies

# To be a candidate for the short list of this study's trade-off study, a sensing technology [must]{.underline} be able to: 

-   make positive identification of both inbound and outbound trucks at
    a matched pair of two points (upstream and downstream) that
    correspond to where data collectors are currently stationed for
    manual readings;

-   time-stamp each vehicle that is positively identified at its
    detected location so as to enable travel time calculations, and;

-   operate in all weather conditions found at a border crossing.

**Table 1. Comparison of Vehicle Sensing Technologies**

+------------------+-------+-------+--------+---------+------+-------+
| Technology       | **T   | **Low | **Not  | **In    | *    | **Pos |
|                  | ravel | V     | P      | clement | *Low | itive |
|                  | T     | olume | rivacy | We      | I    | ID**  |
|                  | ime** | Co    | Inva   | ather** | nfra |       |
|                  |       | unt** | sive** |         | Co   |       |
|                  | *     |       |        |         | st** |       |
|                  | *S/W* |       |        |         |      |       |
|                  | *[^1] |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| # Ultrasonic     |       |       | Yes    |         | Yes  |       |
+------------------+-------+-------+--------+---------+------+-------+
| Microwave        |       | Yes   | Yes    | Yes     | Yes  |       |
| Doppler          |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Microwave True   |       | Yes   | Yes    | Yes     | Yes  |       |
| Presence         |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Passive Infrared |       |       | Yes    |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Active Infrared  |       |       | Yes    |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Visible VIP      |       | Yes   |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Infrared VIP     |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Acoustic Array   |       |       | Yes    |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| SPVD             |       | Yes   | Yes    | Yes     | Yes  |       |
| Magnetometer     |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| AVI Laser        |       |       |        |         | Yes  | Yes   |
+------------------+-------+-------+--------+---------+------+-------+
| AVI RF Active    |       |       |        | Yes     |      | Yes   |
| Tags             |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| AVI RF Passive   |       |       |        | Yes     | Yes  | Yes   |
| Tags             |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| AVI RF Smart     |       |       |        | Yes     |      | Yes   |
| Tags             |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| AVI Smart Cards  | Yes   |       |        | Yes     |      | Yes   |
| with RF          |       |       |        |         |      |       |
| Transponders     |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| AVI IR Tags      |       |       |        | Yes     | Yes  | Yes   |
+------------------+-------+-------+--------+---------+------+-------+
| AVI Smart Cards  |       |       |        | Yes     |      | Yes   |
| with IR          |       |       |        |         |      |       |
| Transponders     |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Enhanced Common  |       | Yes   | Yes    | Yes     | Yes  | Ye    |
| Inductive Loop   |       |       |        |         |      | s[^2] |
+------------------+-------+-------+--------+---------+------+-------+
| Signature        |       | Yes   | Yes    | Yes     | Yes  | Yes   |
| Inductive        |       |       |        |         |      |       |
| Sensors          |       |       |        |         |      |       |
| (Enhanced        |       |       |        |         |      |       |
| Loop-Based       |       |       |        |         |      |       |
| Traffic          |       |       |        |         |      |       |
| Surveillance)    |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Mobile Phone     |       |       |        | Yes     | Yes  | Yes   |
| Locating         |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| License Plate    |       | Yes   |        | Yes     |      | Yes   |
| Reader           |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+
| Vehicle Matching | Yes   | Yes   |        | Yes     |      | Yes   |
| System           |       |       |        |         |      |       |
+------------------+-------+-------+--------+---------+------+-------+

The sensing technology types in Table 1 that meet these essential
criteria are examined in greater detail below. A 'Yes" entry in Table 1
indicates a positive trait. A candidate sensing technology would
[ideally]{.underline} also be:

-   inexpensive to purchase, install, and maintain;

-   not easily vandalized;

-   not seen as invasive of privacy by its users;

-   capable of use without installation outside the U.S. border;

-   able to count [all]{.underline} vehicles that pass (as a collateral
    benefit to the overall border

crossing truck travel time program); and

-   communicate information (or connect to a computer that will) for
    other purposes

> (toll, Customs, etc).

# None of the technologies that are examined below has all of the desired attributes. Furthermore, the only technologies in this list that are currently known to already have software for calculating travel times are the Automatic Vehicle Identification technologies (used for electronic toll collection) and the Vehicle Matching System (which is being used in Europe). However, development of software to work with any of these sensing technology types should be possible without great expense. 

Automatic Vehicle Identification (AVI) refers to the components and
processes of a toll collection system in which the equipment is able to
determine ownership of the vehicle in order to charge a toll to the
proper customer. AVI technology is broken down into three main
categories: Laser, Radio Frequency (RF), and Infrared (IR).

1.  Automatic Vehicle Identification (AVI) Laser

AVI Laser systems read a bar code attached to a vehicle, which is read
by a laser scanner as a vehicle passes through a toll lane. This
technology is susceptible to weather and dirt. Also, the barcode must be
reasonably close to its reader, which reduces the distance over which
this system can work.

2.  AVI Radio Frequency (RF)

## AVI RF systems utilize a transponder tag that is read by an RF reader/antenna. Some RF tags are used for vehicle-to-roadside communications, which can be used to inform the driver of traffic conditions. RF technologies include RF tags, RF smart tags, and smart cards with RFR transponders.

An **RF tag** is a device located in or on the vehicle that is used in
conjunction with an in-lane RF antenna to communicate identifying
information about the vehicle and customer to the toll system. The
information stored in the tag is fixed (read only) and cannot be
changed. The RF tag does not have any processing capability. This type
of tag is referred to as a Type I tag. Some tags have an updateable
(read/write) area on which an antenna/reader may encode information such
as point of entry, date/time of entry, etc.

A RF tag operates in a half duplex mode, which means that it cannot send
and receive data at the same time. The signal that it uses can be
generated in one of two ways: **actively** (in which the RF tag contains
a transmitter and generates its own RF signal) and **passively** (in
which the RF tag modifies and reflects the signal it received from the
antenna/reader. A passive RF tag does not contain a transmitter).

An **RF smart tag** is an RF device located in the vehicle that is used
in conjunction with an in-lane RF antenna/reader to communicate
identifying information about the vehicle, customer, and account balance
to the toll system. Some portions of the tag information are fixed (such
as vehicle and customer data) while others are updateable (such as
account information). The smart tag contains a microprocessor which is
updated each time the smart tag is used. RF smart tags operate in full
duplex mode, meaning that they are able to send and receive data at the
same time. They actively generate the signal used to communicate with
the antenna/receiver via a transmitter.

The **smart card with RF transponder** is an integrated circuit device
that contains a microprocessor and memory and stores account balance
information. For toll collection, smart card use requires the smart card
itself and a separate RF transponder (tag). The RF transponder is a
device located in the vehicle that interfaces to the smart card and
allows the smart card to communicate with the in-lane antenna/reader. In
addition, the transponder contains information about the vehicle that it
transmits to the antenna/reader along with the smart card information.
The tags used with smart cards employ either full or half duplex
communications with active or passive transmissions.

The toll operation at the World Trade Bridge near Laredo, Texas utilizes
smart cards with RF transponders to collect tolls for around 95 per cent
of outbound trucks (i.e., trucks leaving the U.S. for Mexico). There is
an associated weigh-in-motion sensor that helps the toll agency charge
by axle and weight. The weigh-in-motion sensor cable is located
approximately 150 feet from the entrance to the truck tollbooths and
extends across all eight lanes. This is the only smart card/transponder
arrangement on the Mexican border, and it might present a great
opportunity for a pilot test.

With this type of system, each toll lane is equipped with an RF antenna
that is usually mounted in the center of the lane above the roadway. The
reader sends out a signal via the antenna to the tag that lets the tag
know that it should begin communication. The tag returns a unique ID
number that is used to identify the vehicle (customer) to the electronic
toll collection (ETC) system. In the case of read/write tags, smart
tags, or smart cards with an RF transponder, the tag may transmit
additional information such as account balance or point of entry and the
reader may send back updated information to be encoded on the tag/smart
card. The maximum read/write range of RF tags is generally up to about
100 feet. In use, they are usually within 20 to 30 feet of the antenna
during communication.

Advantages of AVI RF sensor technologies include proven technology and
relatively low cost. Disadvantages include infrastructure costs and the
need for cross-border operational agreements.

2.6.3 AVI Infrared (IR)

AVI IR systems utilize an in-vehicle tag that is read by a
reader/transmitter installed in the toll lane. IR technologies include
IR tags and smart cards with IR tags. An **IR tag** -- similar to an RF
tag - is a device located in or on the vehicle that is used in
conjunction with an in-lane IR antenna to communicate identifying
information about the vehicle and customer to the toll system. The
information stored in the tag is fixed (read only) and cannot be
changed. The IR tag does not have any processing capability.

A **smart card with IR tag** essentially operates in the same functional
manner as a smart card with RF tag -- the key difference is its method
of communication (an IR vs. an RF frequency). AVI Infrared technologies
have much the same basic advantages and disadvantages as AVI RF
technologies.

[Border Applications of Automatic Vehicle Identification
Technology]{.underline}

AVI RF and Infrared advantages include proven technology and moderate
cost. Disadvantages include infrastructure costs, some susceptibility to
environmental influences, and the need for cross-border operational
agreements.

4.  **Enhanced Common Inductive Loop**

Loop detectors, are the primary source of quantitative traffic data in
the U.S. They are usually hexagon-shaped wires buried in the road. When
a vehicle passes over a loop detector, its metallic mass causes
fluctuations in the detector's inductance. Until recently, the cards
used with loop inductors only read in a pulse or a presence mode, which
produced a digital output. Using this technology, when the measured
inductance crossed a threshold set in the detector card, its field
controller read it as a digital "one," or occupancy. When the vehicle
moved off of the detector, the field controller then read a digital
"zero," or unoccupied. This technology did not differentiate for the
size of vehicle.

The principal components of an inductive loop detector are one or more
turns of insulated wire buried in a shallow cutout in the roadway, a
lead-in cable that runs from a roadside pull box to the controller, and
an electronics unit located in the controller cabinet. The insulated
wire loop can be excited with a signal ranging in frequency from 10 KHz
to 200 KHz and functions as an inductive element in conjunction with the
electronics unit. The disadvantages of the basic inductive loop
technology include:

-   time and difficulty of installation (involving up to a dozen saw
    cuts),

-   fitting the loop to the cuts without crimping or nicks,

-   changes to inductance caused by the environment,

-   vehicle's offset in a lane, which adversely affects repeatability,

-   vehicles with large differences in inductance, and

-   vehicles changing lanes.

Data supplied by these loop detectors are vehicle presence, count, and
occupancy. When used in pairs to form a "speed trap," they can also
measure speed directly. Two loops placed close together in this way
gauge vehicle speed based on the time between occupancy of the two
sensors. Speed and occupancy can be used to determine a vehicle's
length. When a vehicle stops on or passes over the loop, its inductance
is decreased indicating the presence or passage of a vehicle. The
electronics unit responds to the change in inductance and conveys the
vehicle presence data to the controller when requested. This basic
inductive loop technology was developed in the 1970's and '80's and did
not change much until recently.

However, there are now loop detectors that have the capability to
produce a vehicle inductive signature through a serial port on the
detector card. This unique signature results from the net decrease in
the detector's inductance when the metallic mass of a vehicle passes
over the magnetic field generated by the inductive loop. Inductive
signature analysis can allow vehicle classification data to be derived.
In other words, instead of knowing that some vehicle of indeterminate
size passed over the detector, the characteristics of the signature can
be used to determine whether, for example, the vehicle was a passenger
car or a large truck.

The California Partners for Advanced Transit and Highways (PATH) has
conducted much research into this new technology. PATH took a
three-phased approach to improving this technology. First, they used
existing loop detector hardware but upgraded the communication protocols
and analysis software. The second phase replaced existing loop detector
cards with commercial detector cards capable of outputting a vehicle's
inductive signature. This approach not only permits most vehicles to be
matched, it also gives more accuracy to local counts and vehicle
classifications. It can offset many detector failures by automatically
adapting to changes in loop inductance. Finally, that ability helps to
improve a number of current reliability problems that exist with
inductive loop technology. PATH's third phase intends to use more
advanced detector hardware and simpler, cheaper, more reliable loop
geometries.

There are two different systems that have been developed for classifying
vehicle signatures. One system uses a Self-Organizing Feature Map, which
is an artificial neural network. On a test, this technology was said to
have been able to classify 300 test vehicles with an accuracy of 85
percent (the classes involved were SUV, limousine, bus truck, car towing
trailer, and semi-trailer truck). A second system uses, for
classification, a heuristic discriminant algorithm. This approach was
said to yield 81%-91% overall classification rates in testing.

With these accuracies, inductive signatures can be applied to some new
transportation measures. Data can be derived that were not previously
accessible, including section travel time. Speeds that previously
derived from double inductive loop configurations can now be derived
with single loops by using vehicle inductive signatures. Thus, there are
new ways to collect important real-time data through the use of
inductive signatures. There are a number of new applications that emerge
from this improved technology that are beyond the purpose of this
report.

## Border Applications of Automatic Vehicle identification Technology

Among their advantages, loop detectors are a common, recognizable
sensor. They have relatively inexpensive purchase and installation
costs. One of their disadvantages is that where crossing vehicles are
mostly similar (i.e., large trucks), differentiation will be more
difficult than if there are more diverse vehicle types in the traffic
flow. How accurately this enhanced loop-detection system can positively
identify a specific truck among a throng of other trucks remains to be
seen, so therefore it is a potential drawback.

**2.6.5 Signature Inductive Sensors (Enhanced Loop-Based Traffic
Surveillance)**

One company interviewed in conjunction with this report had an inductive
signature product under development. Their product feature claims
include:

-   single roadway cut installation, which can cover multiple lanes and
    covers lane edge to lane edge;

-   faster, safer, and easier installation (approximately ½ hour vs. 4
    hours);

-   shorter traffic stoppage/impedance times, with minimal travel time
    loss;

-   more defined signature data;

-   uniform data over entire lane of traffic, regardless of vehicle
    lateral offset within the lane; and

-   does not miss turning or off-center vehicles like other loop
    technologies.

[Border Applications of Automatic Vehicle Identification
Technology]{.underline}

The same advantages and disadvantages that applied to the previous
category -- enhanced common inductive loop -- apply to signature
inductive sensors as well. However, this technology is intended to
produce better discrimination among vehicles.

**2.6.6 Mobile Phone Locating**

A recent study has found that 49.5 percent of cellular phone calls were
placed while driving. While the percentage of wireless calls placed by
drivers - compared to those placed in home or office - has declined
somewhat, the number of such calls has grown considerably. There are now
said to be nearly 120 million wireless subscribers in the U.S. The
popularity of cell phone use has given rise to surveillance technology
that uses geolocation of those callers.

The CAPITAL ([C]{.underline}ellular [Ap]{.underline}plied to
[I]{.underline}TS [T]{.underline}racking [a]{.underline}nd
[L]{.underline}ocation) Operational Test and Demonstration Program,
which was conducted in 1994 in the Washington, D.C. metropolitan region,
was one of the first actual field deployments of technology to geolocate
cell phone calls. This ITS operational test made extensive use of the
existing cellular infrastructure for both area wide surveillance and
communications. Equipment was co-located on Bell Atlantic mobile towers
to detect cellular users and geolocate phones on designated roadways.
The project explored questions related to positioning accuracy, incident
detection accuracy, possible applications in a traffic management center
(TMC), and potential for replacing or supplementing certain other
technologies, such as loop detectors and video surveillance. The CAPITAL
operational test represented a first-generation approach to geolocation.
It utilized RF direction finding and required substantial
infrastructure, and it required both line of sight and multiple cell
towers to function.

In the years since the CAPITAL project demonstrated some of the
attractive features of geolocation, the technology has advanced. "New
modes of cellular geolocation are available. The installed base of
cellular telephones is far greater, and includes a wider variety of
cellular protocols, both digital and analog. This affords the
opportunity to focus more directly on transportation management issues,
such as the accuracy of speed estimates derived from dynamic geolocation
measurements, applications to incident detection and management, and
cost-benefit analysis."

Consequently, another mobile call tracking prototype system is currently
being tested in the Washington, D.C. metropolitan region. This ITS
operational test is the Capital Wireless Integrated Network (CapWIN).
Following along the same lines as the CAPITAL project, it implements a
wireless communications network that serves the core mobile
communication functional needs of transportation, law enforcement, fire
and EMS in the Washington metropolitan region. Its network supports
multiple in-vehicle platforms.

Something that has advanced location services is Emergency 911 (or
E-911) calls for emergency assistance. As part of the Federal
Communications Commission's E-911 mandate, all cellular service
providers must be able to accurately estimate the location of incoming
wireless Emergency 911 calls by October 2001. Part of that requirement
is that wireless service providers have the ability to pinpoint and
report to Public Safety Answering Points (PSAPs) the locations of all
911 callers within an accuracy of 100 meters in 67% of all cases.

In response to this need, a company participating in the CapWIN
operational test has developed a technology that allows cellular phone
calls to be tracked and monitored anonymously. The proprietary *Location
Pattern Matching* process used by this system determines a wireless
subscriber's location by measuring the distinct RF patterns and
multi-path characteristics of radio signals arriving at a cell site from
a caller. The technology identifies the unique radio frequency pattern
or "signature" of the call and matches it with a similar pattern stored
in a central database. This system does not require direct line of sight
to multiple base stations to identify locations. Since this system can
use its own antenna arrays to detect RF signals, no alteration to
existing cellular base stations or subscribers' handsets is required.

In operation, "a mobile phone placing a call emits radio signals. The
signals bounce off buildings and other obstacles, reaching their
destination (the base unit) via multiple paths. At the base station, the
(technology) analyzes the unique characteristics of the signal,
including its "multipath" pattern, and compiles a 'signature.' The
signature pattern is compared to a database of previously identified
signature patterns and their corresponding locations, and a match is
made. By matching the signature pattern of the caller's signal with the
database of known signatures, the caller's geographic location is
identified and mapped. By continually updating the location data for
multiple callers on a specified road segment, the speed at that segment
of roadway is computed algorithmically. Speed data (are) stored in a
permanent database that permits historical analysis of traffic flow for
Traffic Management. Additionally, a transient database is available for
real-time display of traffic flow." The system consists of a base unit
and a location pattern-matching database. It requires only one cell site
in an area to function, which means it is also suited to rural sites
where some of the border crossings are located.

The literature of the company providing the location pattern matching
technology states, "Unlike other location technologies under
development, (its) technology eliminates the need for line of sight
triangulation involving multiple cell sites. This is particularly
important in dense urban environments where buildings tend to obstruct
the line of sight, and in sparse rural environments where it is unlikely
that three or more base stations will be available to receive the
caller's signal." The company notes, "more than 70% of the wireless
population currently resides" in those same dense urban environments.

It states that its system "adapts to existing cellular infrastructure
and requires no alteration to the base station or subscriber handsets.
Subscribers will not need to purchase new phones to access services, and
wireless carriers will not need to make expensive infrastructure
investments to offer location-based services." And "information
generated by each (of this system's) Base Unit(s) is downloaded to
centralized database hubs, which route the geolocation information to
Public Safety Answering Points (PSAPs) and other service providers or
call centers."  

Another company uses a related but different approach that derives
traffic information from the routine operational data of cellular
telephone networks - an approach that requires no field hardware
devices. This approach uses mobile phone data that come from multiple
wireless carriers, whose cellular signal data are married with other ITS
data and GIS data. This company asserts that their technology uses
advanced-intelligence software to determine average vehicle speeds,
real-time traffic patterns, and velocity data to determine roadway
conditions. They say that it can deliver that information in real time
to Traffic Management Centers. And in areas with insufficient volume to
determine traffic data, they utilize wireless bandwidth on a limited
basis. This data has been stripped of any customer identity information.

[Border Applications of Automatic Vehicle Identification
Technology]{.underline}

The key advantage to mobile phone locating is that it requires no new
infrastructure. Disadvantages include the dependency on drivers making
calls in sufficient numbers while crossing, from before the first data
collection point through the second. Also, origin/destination
geolocation capability from mobile phone locating is not currently as
accurate as on-site sensors. Whether that accuracy difference is
significant is not currently known.

2.6.7 License Plate Readers (LPRs)

There are many license plate readers already in use at border crossings
at both Mexico and Canada. Both the U.S. and Canada utilize them at
Customs booths for automobiles. None are currently being used for
trucks. They are purchased from the same company and used in the same
manner. These license plate readers are used to record the arrival and
departure of vehicles at the U.S.-Mexico border. This system works by
electronically recording the front and rear plates of vehicles as they
pass through the port. The system then digitizes the information and
sends it to a Customs information database.

A computer checks a national database of stolen cars to see if the plate
numbers match. The computer then alerts Customs officials if the car was
stolen or used in criminal activity. This LPR system reads and
recognizes violators' license plate numbers within milliseconds. The
initial installations focused on first getting LPRs installed for the
lanes inbound from Mexico but law enforcement officers would like to
have the systems in both inbound and outbound lanes.

A license plate reader converts image patterns into previously learned
symbols prior to comparison. Slowly-moving vehicles can pose a greater
challenge to the LPRs because they are more capable of making turning
movements within the sensor's focus.

## Border Applications of Automatic Vehicle Identification Technology

Advantages include a relatively high positive identification rate and
the fact that many LPRs are already in use at Customs facilities, both
in the U.S. and Canada (see figure 7). A portable option is available,
but its portability does not give it as much accuracy as the hardmounted
version. Among the disadvantages, many trucks have multiple license
plates that would confuse the reader, or dirty, damaged, or bent-over
license plates that are more difficult to read. And the portable devices
would be susceptible to vandalism if remote from Customs or toll
operations facilities. LPRs would be a relatively expensive system for a
travel time application.

![](media/image8.jpeg){width="4.444444444444445in"
height="3.3333333333333335in"}

Figure 7. License Plate Reader at the Zaragoza Bridge, El Paso
(Automobile Side)

2.6.8 Vehicle Matching

A vehicle matching system compares image patterns directly without the
requirement to recognize symbols. This means that it does not "read" a
license plate. It works by capturing the images of passing vehicles and
"fingerprinting" each vehicle together with a date, time, and position
stamp. A communications link transmits these fingerprints to an exit
system, which stores them as entry fingerprints. The exit system also
captures vehicle images and creates fingerprints, then matches them.
This technique is used to determine travel time of vehicles that have
been speeding, and then activates a license plate reader to document the
violation and bill the vehicle owner.

A company that provides this technology claims that it:

-   will work with any license plate style or type;

-   does not need to be re-programmed if new plates are issued;

-   is not affected by trailer hitches, license plate frames, etc.;

-   uses more information than just plate characters;

-   can perform matches on vehicles without visible license plates; and

-   works whether the vehicle has a computer-readable license plate or
    not.

This product uses a laser ranger to detect passing vehicles, which
triggers a camera. Vehicle images are captured by this advanced digital
video camera, whose controls are constantly adjusted by a smart light
sensor. This light sensor adjusts camera parameters for optimum license
plate and vehicle contrast regardless of ambient illumination
conditions. It decides when to turn nighttime illumination on or off. It
uses a light flash that is filtered to be invisible to drivers and which
illuminates the entire vehicle, not just the license plate.

## Border Applications of Automatic Vehicle Identification Technology

Among the advantages, there is a very high probability of
identification. There is also a portable version of this system
available. It involves a trailer that positions an arm with the sensing
technology equipment over two lanes of traffic. However, the portable
version ideally needs a downlook angle from overhead to fingerprint
moving trucks effectively. Among the disadvantages, Vehicle Matching
would be a relatively expensive system for a travel time application.

2.  OTHER CONSIDERATIONS

**3.1 Cost**

The cost of a system that automates the detection of trucks and the
calculation of their travel time must take into account that the
information it derives might be part of a larger, more detailed
information-providing system and that the continuous data might be more
valuable than sporadic visits. The costs of an automated system must
therefore be measured against the recurring and non-recurring costs from
having a team of data collectors travel to a site for one, or perhaps
two, data collection cycles per year. Rather, the automated system
(depending upon the configuration chosen) could yield data on an hourly
basis for every day of operation throughout the year. The value of that
data must be weighed against the system cost on some type of
amortization schedule.

The opportunities to leverage concurrent use of technologies that emerge
from local, state, and federal uses as well as from the response to the
terrorist threat should be a key part of any deployment. In fact, it may
be appropriate to study the operating, trade, and security-related
technologies that are being considered in terms of potential dual-use
technology.

**3.2 Maturity of the technologies for deployment**

Any of the technologies in Table 2 could probably be made to work in the
application of vehicle identification and travel time calculation. Most
would require some non-recurring effort to design software for those
applications. Most of the candidate technologies are mature in at least
a related use. Some are still being developed but appear to be well
along the path to achieving reliable results in the field.

**3.3 Site security/vandalism**

Equipment security is a concern. Should equipment be located outside of
Customs property, whether permanently mounted or portable, it may be
subject to theft or vandalism. For example, this would be a concern if a
sensor were located well upstream in the flow of traffic due to a long
queue. That is currently the situation as increased security concerns
are causing delays at the border crossings for all vehicles.

**3.4 Privacy**

Many recent articles have dealt with the issue of privacy and commuters.
There is a transportation system in New York that tracks cars that have
electronic tollbooth tags, to help gauge speeds and congestion. In the
Washington area, an ITS project (section 2.6.6 above refers) allows
transportation officials to monitor movement of drivers talking on cell
phones. There is even equipment that "sniffs" passing cars to identify
which radio stations motorists have chosen.

Combined with the September 11 terrorist attacks, there is
understandably increased interest by government organizations in what
members of society are doing. Some of the same technologies that help us
respond to incidents and manage congestion can reveal information about
the driver. One example is the use of cameras to snap photos of cars
that run red lights, and there are sites where cars that are out of
standards for emissions are photographed automatically. Closed circuit
television cameras are increasingly used to monitor roads; as their
resolution gradually improves, they could be used to automatically match
vehicle occupants' faces to reference databases. (Note: some uses of the
technologies above have been legally -- and successfully -- challenged).
Some on-board navigation systems allow vehicles to be tracked. The
mobile phone location matching discussed above takes care to remove any
identification of the driver, but many drivers are aware that such a
system is tracking their vehicle. Law enforcement authorities at many
border crossings in fact, use the license plate readers that are also
discussed above, for the principal purpose of identifying lawbreakers
attempting to cross.

For all of these reasons, truck drivers may feel anxiety about a visible
automated technology, particularly when it first appears. Government
organizations like Customs or toll operations may find it prudent to get
acknowledgement from unions or trucking associations of any automated
technology used to determine travel time. Those groups may need to be
reassured that the technologies are not an attempt to identify, conduct
surveillance, or otherwise invade the privacy of the truckers who are
their members. In the current climate, there will be a natural tendency
to suspect that any new technology has something to do with security.

5.  **Portability**

For some types of devices, portability offers advantages if equipment
were truly "plug-and-play." If automated sensing was not needed
full-time, the equipment could be used temporarily then moved to another
site. However, not all technical approaches have infrastructure that
fall into this category. Even with those that do, the sensitivity of the
equipment may not reasonably lend itself to any approach beside a
permanent installation. And security is also a concern.

6.  Hourly count data

Due to the difficulty that Battelle and others have experienced getting
hourly truck travel information from some crossings, particularly from
the Mexican side, it would be useful to collect ongoing hourly counts.
Some of the sensing technologies like the signature inductive have the
capability to count vehicles. Without this inherent capability in the
technology, it may be desirable to set up "semi-permanent" inductive
loops or pneumatic tubes at the crossings to count hourly traffic.
Ideally these would be at the same locations on both sides of the
border, for example around the tollbooths (where traffic outbound from
the U.S. is tabulated, although not all crossings have toll operations).

However, recognizing that other national governments would be involved,
these loops or pneumatic tubes could all be on the U.S. Customs side of
a crossing for expediency. If that approach is taken, however, there
would be errors in comparing outbound and inbound travel that are
induced by positional differences. Since the pneumatic tubes would all
have to be on the same side of the border, they would not be not at the
same upstream-downstream positioning as the ideal tollbooth--primary
inspection pairing. But the error would perhaps not be significant for
the purpose intended: determining patterns.

7.  Developments Since 9/11

Following the terrorist attacks in New York and Washington, additional
security measures at the border crossings resulted in delays that
produced significantly longer travel times, particularly for traffic
inbound to the U.S. Work-around measures were implemented to alleviate
the congestion created, recognizing the detrimental effect that the
condition was having on trade. A December 18, 2001 article in the El
Paso Times discussed a homeland security approach being considered that
could perhaps affect the selection of a technology to automate truck
travel time determination.

"Under the coordinated agenda, truck drivers, motorists, and pedestrians
would be issued 'Smart Cards,' which have been mainly used by commuter
lane traffic. The cards contain biometric information and photo images,
which can be checked in seconds by computer and verified by port
officials. In addition to the cards, scanners - 12 for trucks and
vehicles - would be used to peer into semi trucks as well as into autos
to examine their contents. At least 20 scanners would be used to check
motorists and pedestrians."

".....the Ysleta (note: also known as the Zaragoza) port of entry in far
east El Paso is the second largest in the state." "...it would cost
about \$18 million to outfit the (Ysleta/Zaragoza) crossing with
personnel, scanners, and other high-tech equipment."

As mentioned in section 2, smart cards with RF transponders are already
used by most of the truck drivers passing through the tollbooths of the
World Trade Bridge border crossing to pay tolls as they leave the U.S.
If these newer smart cards with biometric information are used at all
border crossings, they could in theory be adapted to support toll
collection as well as register a timestamp through recording equipment.
If so - and if Customs agencies support the idea -- such smart cards
might be the technology of choice for automating the truck travel time
process. Of course, there would need to be an agreement with Mexico and
Canada to allow equipment to be installed in order to read both points
in a matched pair of sectional travel locations.

3.  **TRADE-OFF MATRIX**

The sensing technologies delineated in Table 1 that appear to meet the
essential operational criteria of positive identification in a matched
pair of collection points, time-stamping, and all-weather operation, are
compared in Table 2. This assessment assumes that any of the
technologies in Table 2 will perform technically in an acceptable manner
and that software with which to calculate travel time can be developed
(if it is not already in use for that purpose). The format is a
stoplight chart that makes subjective judgments about how nearly the
sensing technology meets the ideal.

A green circle indicates the best category of performance in a
particular category. A red square may indicate the least amount of
performance in that category or it may mean inability to perform in that
category, depending on the context. Red, for example, does not indicate
a show-stopping inability that would preclude the use of that particular
technology but rather a relative perspective of how it compares to the
other technologies compared to cost, convenience, or collateral
features. Thus, some red in a given row does not signify that the
technology cannot be expected to perform in that application. There is
no technology listed in Table 2 that does not have some red. A yellow
triangle signifies an intermediate position; for example, it may
indicate progress toward meeting a need but something short of a mature
technology for the application.

Table 2 therefore focuses more on practical aspects of a limited number
of sensing technologies, any one of which should be able to perform the
functions required. The comparison assumes that AVI technologies (e.g.,
smart cards with RF transponders) are not used with all vehicles.
Likewise, not all drivers will be using their cell phones as they cross
the border. As the Table 2 footnote 1 explains, two of the categories
have no intermediate positions: a technology either fits the category or
it doesn't.

# 

**Table 2. Summary Matrix of Candidate Sensing Technologies**

+-----------+----------+--------+---------+-----------+------+------+
| T         | **Geoloc | **% of | **Cross | **Mature  | *    | *    |
| echnology | ation/** | Ve     | -Border | T         | *Inf | *Tot |
|           |          | hicles | Install | echnology | ra-s | al** |
|           | **Travel | Reco   | ation** | for**     | truc |      |
|           | Time**   | rded** |         |           | t.** | **   |
|           |          |        | **      | **Appl    |      | Hour |
|           | **Ac     |        | Require | ication** | **Co | ly** |
|           | curacy** |        | d**[^3] |           | st** |      |
|           |          |        |         |           |      | *    |
|           |          |        |         |           |      | *Cou |
|           |          |        |         |           |      | nt** |
|           |          |        |         |           |      | [^4] |
+-----------+----------+--------+---------+-----------+------+------+
| AVI Laser |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| AVI RF    |          |        |         |           |      |      |
| tags      |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| AVI RF    |          |        |         |           |      |      |
| Smart     |          |        |         |           |      |      |
| Tags      |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| AVI Smart |          |        |         |           |      |      |
| Cards     |          |        |         |           |      |      |
| with RF   |          |        |         |           |      |      |
| Transd    |          |        |         |           |      |      |
| ucers[^5] |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| AVI IR    |          |        |         |           |      |      |
| Tags      |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| AVI Smart |          |        |         |           |      |      |
| Cards     |          |        |         |           |      |      |
| with IR   |          |        |         |           |      |      |
|           |          |        |         |           |      |      |
| Transd    |          |        |         |           |      |      |
| ucers[^6] |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| Common    |          |        |         |           |      |      |
| Inductive |          |        |         |           |      |      |
| Loop      |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| Signature |          |        |         |           |      |      |
| Inductive |          |        |         |           |      |      |
| Sensors   |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| Mobile    |          |        |         |           |      |      |
| Phone     |          |        |         |           |      |      |
| Locating  |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| License   |          |        |         |           |      |      |
| Plate     |          |        |         |           |      |      |
| Reader    |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+
| Vehicle   |          |        |         |           |      |      |
| Matching  |          |        |         |           |      |      |
| System    |          |        |         |           |      |      |
+-----------+----------+--------+---------+-----------+------+------+

= Green (best performance) = Yellow (intermediate) = Red (poor)

# 

**5.0 CONCLUSIONS**

The main objective of this study has been to determine what sensor
technologies could potentially replace or supplement trained data
collectors, in an automated system to calculate (or help calculate)
truck travel times at border crossing sites. To perform that role, a
selected technology will have to (1) identify specific trucks, (2)
timestamp them as they pass a matched pair of predetermined upstream and
downstream point in a direction of flow, (3) collect and process the
resultant travel time information, and (4) archive it in a format
available for an end-user -- i.e., the FHWA, other federal, state, and
local agencies, and perhaps supporting organizations.

Appendix A summarizes the advantages and disadvantages of the border
application candidate technologies that have been discussed in sections
2.6.1 through 2.6.8. All of the technologies except one share a
significant disadvantage: they require infrastructure to be installed on
both sides of the border. Installation entails cross-border agreements
as well as expense. With some of the candidate technologies, operational
cooperation may also be required, such as agreement with trucking firms
and unions to use a certain kind of tag. The only technology type that
doesn't require cross-border infrastructure has its own unique set of
disadvantages. Most of the technologies would have to be configured to
perform in a manner that is not what they are developed for, but the
similarity is close enough that risk should be controllable.

A modest follow-on study to determine the most appropriate sensor
technologies for the FHWA's needs could produce benefits. In particular,
there are currently serious considerations being given to various
technologies for personnel identification and tracking under the aegis
of Homeland Defense. A marriage, between some of those proposed
security-based technologies with technologies that could help FHWA
leverage its desire to automate travel time calculation, is perhaps a
rare window of opportunity that is presenting itself.

6.0 REFERENCES

Mobility Monitoring: Review of Current Practice and Program Outline,
Chapter 3: Implementing a Travel-Time Based Border Freight Roadway
Transportation Performance Measure

Development of IVHS Traffic Parameter specification; Task A report for
*Detection Technology for IVHS*, Contract Number DTFH61-91-C-00076

Detection Technology for IVHS, Volume 1: Final Report, Publication No.
FHWA-RD-95-100, December 1996

ETTM (Electronic Toll Collection and Traffic Management) on the Web,
[http://www.ettm.com](http://www.ettm.com/) as of December 19, 2001

Intelligent Surveillance Using Inductive Vehicle Signatures,
*Intellimotion*, vol. 8 no. 3, 1999 (Carlos Sun, PATH/Rowan University)

"Transportation Management Applications of Anonymous Mobile Call
Sampling," presented and published at the ITS America 11^th^ Annual
Meeting and Exposition, June 2001 (Dr. Brian L. Smith, Michael Pack, Dr.
David J. Lovell, Dr. M. William Sermons)

Appendix A

Trade-Off Comparison of Automated Technologies

+-------------+-------------+--------------+-------------------------+
| Technology  | #######     | ####### D    | ####### Comment         |
|             |  Advantages | isadvantages |                         |
+=============+=============+==============+=========================+
| Automatic   | Truck need  | Weather and  | Reads bar code attached |
| Vehicle     | only have   | dirt can     | to truck. Laser scans   |
| Ide         | bar code    | hinder read. | as vehicle passes.      |
| ntification | attached.   | Bar code and |                         |
| Laser       | Available   | reader must  |                         |
|             | laser       | be close to  |                         |
|             | technology  | one another. |                         |
|             | used.       |              |                         |
+-------------+-------------+--------------+-------------------------+
| AVI Radio   | Although    | Generally,   | Transponder tag in/on   |
| Frequency   | passive,    | tag data are | vehicle. Read by RF     |
| (RF) - tag  | some tags   | fixed and    | reader or antenna. May  |
|             | have        | u            | either *transmit* (tag  |
|             | "write"     | nchangeable; | contains transmitter    |
|             | area        | can only be  | and generates RF        |
|             | permitting  | read. No     | signal); or *receive*   |
|             | encoding of | processing   | (tag reacts to received |
|             | some info   | capability.  | RF from antenna; lacks  |
|             | (entry      | Cannot       | transmitter)            |
|             | point,      | si           |                         |
|             | date/time   | multaneously |                         |
|             | of entry)   | read/send    |                         |
|             |             | info.        |                         |
+-------------+-------------+--------------+-------------------------+
| AVI Radio   | Can         | Cannot       | On-vehicle, used in     |
| Frequency   | s           | update       | conjunction with        |
| (RF) -      | end/receive | customer/    | "in-lane" RF            |
| smart tag   | at same     |              | antenna/reader.         |
|             | time.       | vehicle      | Communicates:           |
|             | Actively    | information  | vehicle/customer info,  |
|             | generate    |              | account balance to toll |
|             | signal that |              | system.                 |
|             | c           |              | Vehicle/customer data   |
|             | ommunicates |              | fixed; other tag info   |
|             | with        |              | updatable (e.g.,        |
|             | anten       |              | account status).        |
|             | na/receiver |              | Contains microprocessor |
|             |             |              | which updates with tag  |
|             |             |              | usage.                  |
+-------------+-------------+--------------+-------------------------+
| AVI Radio   | Generates   | Requires     | Integrated circuit.     |
| Frequency   | its own     | both smart   | Contains                |
| (RF) -      | signal. Can | card and     | microprocessor, memory. |
| smart card  | operate in  | separate RF  | Stores account balance. |
| w/ RF       | either full | transponder  | RF transponder located  |
| transponder | or half     | (tag)        | in-vehicle; transponder |
|             | duplex      | in-vehicle.  | interfaces with smart   |
|             | co          |              | card, permits communi-  |
|             | mmunication | Requires     | cation with             |
|             | mode (i.e., | in           | antenna/receiver on     |
|             | either      | frastructure | card info, vehicle      |
|             | s           | investment   | info.                   |
|             | end-receive | and carrier  |                         |
|             | sim         | purchase of  | Used at LAREDO World    |
|             | ultaneously | card,        | Trade Bridge to collect |
|             | **or** send | transponder. | 95% outbound truck      |
|             | or          |              | data; also provides WIM |
|             | receive).   | Requires     | data to roadside        |
|             | Can receive | cross-border | sensor.                 |
|             | and encode  | operational  |                         |
|             | updated     | agreement.   |                         |
|             | info on     |              |                         |
|             | card.       |              |                         |
|             |             |              |                         |
|             | Proven      |              |                         |
|             | technology, |              |                         |
|             | low cost    |              |                         |
+-------------+-------------+--------------+-------------------------+
| AVI         | Proven      | Read-only.   | Relies on IR frequency, |
| Infrared    | technology, | No           | rather than RF, for     |
| (IR) -- IR  | relatively  | processing   | communication.          |
| tag         | low cost    | capability.  | In-vehicle tag, read by |
|             |             |              | reader/transmitter in   |
|             |             |              | toll lane. Used with    |
|             |             |              | in-lane IR antenna that |
|             |             |              | provides vehicle,       |
|             |             |              | customer info to toll   |
|             |             |              | system.                 |
+-------------+-------------+--------------+-------------------------+
| AVI         | Generates   | In           | Relies on IR frequency, |
| Infrared    | own signal. | frastructure | rather than RF, for     |
| (IR) --     | Provides    | costs.       | communication. Same as  |
|             | for         |              | RF transponder and      |
| Smart card  | co          | E            | smart card.             |
| w/ IR tag   | mmunication | nvironmental |                         |
|             | to/from     | interference |                         |
|             | antenn      | a            |                         |
|             | a/receiver. | possibility. |                         |
|             | Can         |              |                         |
|             | receive,    | Requires     |                         |
|             | encode      | cross-border |                         |
|             | updated     | operational  |                         |
|             | info on     | agreement    |                         |
|             | card        |              |                         |
+-------------+-------------+--------------+-------------------------+
|             |             |              |                         |
+-------------+-------------+--------------+-------------------------+
| Enhanced    | Provides    | Generally    | Generally hex-shaped    |
| Common      | indication  | does not     | wires, buried in road.  |
| Inductive   | of vehicle  | d            |                         |
| Loop        | presence,   | ifferentiate | Vehicle passage causes  |
|             | count, and  | size or type | fluctuations in         |
|             | occupancy.  | of vehicle.  | detector's electrical   |
|             | Paired, can | Time and     | inductance.             |
|             | measure     | difficulty   |                         |
|             | speed.      | of wire      | California PATH         |
|             |             | i            | researching. Its        |
|             | Older       | nstallation. | upgraded protocols and  |
|             | technology; |              | software, using         |
|             | in use.     | Environment  | detector card,          |
|             | Updated     | can affect   | apparently permit       |
|             | versions    | inductance   | vehicle matching as     |
|             | demonstrate | reading.     | vehicle moves through   |
|             | ability to  |              | processing, improving   |
|             | measure     | Vehicle      | local count & vehicle   |
|             | travel      | position     | classification          |
|             | time.       | also affects | accuracy.               |
|             |             | reading if   |                         |
|             | Relatively  | offset or    | Two different systems   |
|             | inexpensive | changing     | developed.              |
|             | purchase    | lanes while  |                         |
|             | and         | crossing     |                         |
|             | i           |              |                         |
|             | nstallation | When         |                         |
|             | costs.      | crossing     |                         |
|             |             | vehicles     |                         |
|             | Some        | similar      |                         |
|             | updated     | (e.g., all   |                         |
|             | versions    | CMVs),       |                         |
|             | can         | dif          |                         |
|             | identify a  | ferentiation |                         |
|             | vehicle     | among them   |                         |
|             | "           | difficult.   |                         |
|             | signature"; |              |                         |
|             | inductive   |              |                         |
|             | signature   |              |                         |
|             | analysis    |              |                         |
|             | can         |              |                         |
|             | classify    |              |                         |
|             | vehicle as  |              |                         |
|             | to truck or |              |                         |
|             | car.        |              |                         |
+-------------+-------------+--------------+-------------------------+
| Enhanced    | Uniform     | Similar to   | Covers roadway, edge to |
| Loop-Based  | data across | above.       | edge.                   |
| Traffic     | lanes of    |              |                         |
| S           | traffic,    |              |                         |
| urveillance | despite     |              |                         |
| (Signature  | lateral     |              |                         |
| Inductive   | off         |              |                         |
| Sensors)    | set/turning |              |                         |
|             | vehicles.   |              |                         |
|             |             |              |                         |
|             | Faster      |              |                         |
|             | in          |              |                         |
|             | stallation; |              |                         |
|             | more        |              |                         |
|             | defined     |              |                         |
|             | signal      |              |                         |
|             | data.       |              |                         |
|             | Ideal:      |              |                         |
|             | better      |              |                         |
|             | dis         |              |                         |
|             | crimination |              |                         |
|             | among       |              |                         |
|             | vehicles.   |              |                         |
+-------------+-------------+--------------+-------------------------+
| Mobile      | No new      | Requires RF  | CAPITAL ops test,       |
| Phone       | inf         | direction    | Washington, D.C. 1994.  |
| Locating    | rastructure | finding,     |                         |
|             | required.   | in           | Capital Wireless        |
|             |             | frastructure | Integrated Network      |
|             | Can track   | (multiple    | (CapWIN) followed,      |
|             | vehicle     | towers) in   | demonstrating potential |
|             | location.   | basic        | of phone monitoring.    |
|             | Later       | technology.  |                         |
|             | versions    |              | CapWIN spin-off         |
|             | don't       | Depends upon | technology may simplify |
|             | require     | callers      | location issue. Employs |
|             | li          | making       | (1) measuring distinct  |
|             | ne-of-sight | sufficient   | RF patterns from        |
|             | tr          | calls; on    | caller's phone and (2)  |
|             | iangulation | border, must | evaluating multi-path   |
|             | of signal.  | be enough    | characteristics of      |
|             |             | made between | radio signals arriving  |
|             | Latest      | monitoring   | at cell site from       |
|             | technology  | points to    | caller (i.e., via       |
|             | permits     | provide      | buildings, other        |
|             | continual   | significant  | obstructions off which  |
|             | updating of | time and     | signal bounces). Would  |
|             | data from   | delay data.  | alleviate need for      |
|             | multiple    |              | line-of-sight to        |
|             | callers     | Current      | determine location of   |
|             | along a     | origin       | call.                   |
|             | roadway to  | /destination |                         |
|             | identify    | geo-location | Related new technology  |
|             | speed.      | capability   | takes mobile phone data |
|             | Permits     | from mobile  | from multiple wireless  |
|             | historic    | phone not as | carriers, links with    |
|             | analysis of | accurate as  | other ITS and GIS data, |
|             | speed data  | on-site      | determining: average    |
|             | from stored | sensors \[is | vehicle speed;          |
|             | inputs, as  | this problem | real-time traffic       |
|             | well as     | if           | patterns, & velocity    |
|             | "real-time" | sampling?\]  | data as means to        |
|             | display of  |              | determine roadway       |
|             | traffic     |              | conditions.             |
|             | flow. Needs |              |                         |
|             | only one    |              |                         |
|             | cell site   |              |                         |
|             | rather than |              |                         |
|             | multiple    |              |                         |
|             | towers in   |              |                         |
|             | rural       |              |                         |
|             | locales,    |              |                         |
|             | such as     |              |                         |
|             | borders.    |              |                         |
+-------------+-------------+--------------+-------------------------+
| License     | Already in  | Not now      | LPRs electronically     |
| Plate       | use along   | available    | read automobile's       |
| Readers     | northern    | for truck    | front, rear plates;     |
|             | and         | monitoring.  | provide input to        |
|             | southern    |              | Customs in digital      |
|             | borders by  | For border   | format. Used by Customs |
|             | Customs for | monitoring,  | to check for stolen     |
|             | automobile  | existing     | cars, criminal usage.   |
|             | review.     | reader       |                         |
|             |             | *locations*  | Initial use by Customs: |
|             | Millisecond | at border    | vehicle entering from   |
|             | ide         | crossing may | Mexico. Future: both    |
|             | ntification | not satisfy  | directions.             |
|             | of suspect  | sampling     |                         |
|             | car.        | requirements |                         |
|             |             | of this      |                         |
|             | High        | border       |                         |
|             | positive    | reviews.     |                         |
|             | ide         |              |                         |
|             | ntification | Slow-moving  |                         |
|             | rate        | or turning   |                         |
|             | alleged.    | vehicle      |                         |
|             |             | causes       |                         |
|             | Portable    | misreading.  |                         |
|             | version     |              |                         |
|             | available.  | Portable     |                         |
|             |             | unit not as  |                         |
|             |             | accurate.    |                         |
|             |             |              |                         |
|             |             | Trucks may   |                         |
|             |             | confuse      |                         |
|             |             | reader with  |                         |
|             |             | multiple     |                         |
|             |             | plates, or   |                         |
|             |             | d            |                         |
|             |             | amaged/dirty |                         |
|             |             | ones.        |                         |
|             |             | Placement of |                         |
|             |             | unit for     |                         |
|             |             | truck        |                         |
|             |             | monitoring   |                         |
|             |             | may be more  |                         |
|             |             | difficult    |                         |
|             |             | than for     |                         |
|             |             | cars.        |                         |
|             |             |              |                         |
|             |             | Units        |                         |
|             |             | vulnerable   |                         |
|             |             | to theft, so |                         |
|             |             | security an  |                         |
|             |             | issue.       |                         |
|             |             |              |                         |
|             |             | Cost high    |                         |
|             |             | for travel   |                         |
|             |             | time         |                         |
|             |             | evaluation.  |                         |
+-------------+-------------+--------------+-------------------------+
| Vehicle     | Allegedly   | Would        | Trailer employs "arm"   |
| Matching    | high        | provide      | with sensing technology |
| System      | probability | "downward"   | over 2 lanes of         |
|             | of vehicle  | view of      | traffic.                |
|             | iden        | commercial   |                         |
|             | tification. | vehicle.     | Compares image patterns |
|             |             |              | of individual vehicle,  |
|             | Portable    | Expensive    | "fingerprinting" w/     |
|             | version     | for travel   | time, date, position    |
|             | available.  | time         | stamp. These            |
|             |             | evaluation.  | communicated to exit    |
|             |             |              | system, which stores    |
|             |             |              | and compares to vehicle |
|             |             |              | as exits. Now used for  |
|             |             |              | speeding verification.  |
|             |             |              | License plate reader    |
|             |             |              | used to document        |
|             |             |              | offense.                |
|             |             |              |                         |
|             |             |              | Allegedly can work with |
|             |             |              | any kind of license     |
|             |             |              | plate.                  |
|             |             |              |                         |
|             |             |              | Relies upon laser to    |
|             |             |              | detect vehicles, which  |
|             |             |              | activates camera that   |
|             |             |              | captures video image.   |
+-------------+-------------+--------------+-------------------------+

[^1]: Refers to travel time software currently in use.

[^2]: Enhancement involves circuit card.

[^3]: ^1^ Installation either required or not.

[^4]: ^2^ Technology either counts every vehicle or not.

[^5]: ^3^ This technology is in use at some border crossings for toll
    purposes.

[^6]: ^3^