![](media/image1.wmf){width="1.25in" height="0.9465277777777777in"}

**August 2006**

**U.S. Department**

**Of Transportation**

![](media/image3.png){width="2.81875in"
height="1.832638888888889in"}**Real-time Bus Arrival Information
Systems**

**Return-on-Investment Study**

**Final Report**

![Sample of Real-Time Information Website (Transit
Tracker)](media/image4.png){width="2.806299212598425in"
height="1.8055118110236221in"}

+----------------+-----+----------+-----------+---+---+-----------------+
| **REPORT       |     |          |           | * |   |                 |
| DOCUMENTATION  |     |          |           | F |   |                 |
| PAGE**         |     |          |           | o |   |                 |
|                |     |          |           | r |   |                 |
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|                |     |          |           | * |   |                 |
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|                |     |          |           | * |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| Public         |     |          |           |   |   |                 |
| reporting      |     |          |           |   |   |                 |
| burden for     |     |          |           |   |   |                 |
| this           |     |          |           |   |   |                 |
| collection of  |     |          |           |   |   |                 |
| information is |     |          |           |   |   |                 |
| estimated to   |     |          |           |   |   |                 |
| average 1 hour |     |          |           |   |   |                 |
| per response,  |     |          |           |   |   |                 |
| including the  |     |          |           |   |   |                 |
| time for       |     |          |           |   |   |                 |
| reviewing      |     |          |           |   |   |                 |
| instructions,  |     |          |           |   |   |                 |
| searching      |     |          |           |   |   |                 |
| existing data  |     |          |           |   |   |                 |
| sources,       |     |          |           |   |   |                 |
| gathering and  |     |          |           |   |   |                 |
| maintaining    |     |          |           |   |   |                 |
| the data       |     |          |           |   |   |                 |
| needed, and    |     |          |           |   |   |                 |
| completing and |     |          |           |   |   |                 |
| reviewing the  |     |          |           |   |   |                 |
| collection of  |     |          |           |   |   |                 |
| information.   |     |          |           |   |   |                 |
| Send comments  |     |          |           |   |   |                 |
| regarding this |     |          |           |   |   |                 |
| burden         |     |          |           |   |   |                 |
| estimate or    |     |          |           |   |   |                 |
| any other      |     |          |           |   |   |                 |
| aspect of this |     |          |           |   |   |                 |
| collection of  |     |          |           |   |   |                 |
| information,   |     |          |           |   |   |                 |
| including      |     |          |           |   |   |                 |
| suggestions    |     |          |           |   |   |                 |
| for reducing   |     |          |           |   |   |                 |
| this burden,   |     |          |           |   |   |                 |
| to Washington  |     |          |           |   |   |                 |
| Headquarters   |     |          |           |   |   |                 |
| Services,      |     |          |           |   |   |                 |
| Directorate    |     |          |           |   |   |                 |
| for            |     |          |           |   |   |                 |
| Information    |     |          |           |   |   |                 |
| Operations and |     |          |           |   |   |                 |
| Reports, 1215  |     |          |           |   |   |                 |
| Jefferson      |     |          |           |   |   |                 |
| Davis Highway, |     |          |           |   |   |                 |
| Suite 1204,    |     |          |           |   |   |                 |
| Arlington, VA  |     |          |           |   |   |                 |
| 22202-4302,    |     |          |           |   |   |                 |
| and to the     |     |          |           |   |   |                 |
| Office of      |     |          |           |   |   |                 |
| Management and |     |          |           |   |   |                 |
| Budget,        |     |          |           |   |   |                 |
| Paperwork      |     |          |           |   |   |                 |
| Reduction      |     |          |           |   |   |                 |
| Project        |     |          |           |   |   |                 |
| (0704-0188),   |     |          |           |   |   |                 |
| Washington, DC |     |          |           |   |   |                 |
| 20503.         |     |          |           |   |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 1\. AGENCY USE |     | 2\.      |           | 3 |   |                 |
| ONLY (Leave    |     | REPORT   |           | \ |   |                 |
| blank)         |     | DATE     |           | . |   |                 |
|                |     |          |           | R |   |                 |
|                |     | August   |           | E |   |                 |
|                |     | 2006     |           | P |   |                 |
|                |     |          |           | O |   |                 |
|                |     |          |           | R |   |                 |
|                |     |          |           | T |   |                 |
|                |     |          |           | T |   |                 |
|                |     |          |           | Y |   |                 |
|                |     |          |           | P |   |                 |
|                |     |          |           | E |   |                 |
|                |     |          |           | A |   |                 |
|                |     |          |           | N |   |                 |
|                |     |          |           | D |   |                 |
|                |     |          |           | D |   |                 |
|                |     |          |           | A |   |                 |
|                |     |          |           | T |   |                 |
|                |     |          |           | E |   |                 |
|                |     |          |           | S |   |                 |
|                |     |          |           | C |   |                 |
|                |     |          |           | O |   |                 |
|                |     |          |           | V |   |                 |
|                |     |          |           | E |   |                 |
|                |     |          |           | R |   |                 |
|                |     |          |           | E |   |                 |
|                |     |          |           | D |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 4\. TITLE AND  |     |          |           |   | 5 |                 |
| SUBTITLE       |     |          |           |   | \ |                 |
|                |     |          |           |   | . |                 |
| Real-time Bus  |     |          |           |   | F |                 |
| Arrival        |     |          |           |   | U |                 |
| Information    |     |          |           |   | N |                 |
| Systems        |     |          |           |   | D |                 |
| Return         |     |          |           |   | I |                 |
| -on-Investment |     |          |           |   | N |                 |
| Study          |     |          |           |   | G |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | U |                 |
|                |     |          |           |   | M |                 |
|                |     |          |           |   | B |                 |
|                |     |          |           |   | E |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | S |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 6\. AUTHOR(S)  |     |          |           |   |   |                 |
|                |     |          |           |   |   |                 |
| Laura Cham,    |     |          |           |   |   |                 |
| Georges        |     |          |           |   |   |                 |
| Darido, David  |     |          |           |   |   |                 |
| Jackson,       |     |          |           |   |   |                 |
| Richard Laver, |     |          |           |   |   |                 |
| Donald Schneck |     |          |           |   |   |                 |
| (Booz Allen    |     |          |           |   |   |                 |
| Hamilton)      |     |          |           |   |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 7\. PERFORMING |     |          |           |   | 8 |                 |
| ORGANIZATION   |     |          |           |   | \ |                 |
| NAME(S) AND    |     |          |           |   | . |                 |
| ADDRESS(ES)    |     |          |           |   | P |                 |
|                |     |          |           |   | E |                 |
| Booz Allen     |     |          |           |   | R |                 |
| Hamilton, Inc. |     |          |           |   | F |                 |
|                |     |          |           |   | O |                 |
| 8283           |     |          |           |   | R |                 |
| Greensboro     |     |          |           |   | M |                 |
| Drive          |     |          |           |   | I |                 |
|                |     |          |           |   | N |                 |
| McLean, VA     |     |          |           |   | G |                 |
| 22102          |     |          |           |   | O |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | G |                 |
|                |     |          |           |   | A |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | I |                 |
|                |     |          |           |   | Z |                 |
|                |     |          |           |   | A |                 |
|                |     |          |           |   | T |                 |
|                |     |          |           |   | I |                 |
|                |     |          |           |   | O |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | E |                 |
|                |     |          |           |   | P |                 |
|                |     |          |           |   | O |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | T |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | U |                 |
|                |     |          |           |   | M |                 |
|                |     |          |           |   | B |                 |
|                |     |          |           |   | E |                 |
|                |     |          |           |   | R |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 9\.            |     |          |           |   | 1 |                 |
| SPONSOR        |     |          |           |   | 0 |                 |
| ING/MONITORING |     |          |           |   | \ |                 |
| AGENCY NAME(S) |     |          |           |   | . |                 |
| AND            |     |          |           |   | S |                 |
| ADDRESS(ES)    |     |          |           |   | P |                 |
|                |     |          |           |   | O |                 |
| Federal        |     |          |           |   | N |                 |
| Transit        |     |          |           |   | S |                 |
| Administration |     |          |           |   | O |                 |
|                |     |          |           |   | R |                 |
| U.S.           |     |          |           |   | I |                 |
| Department of  |     |          |           |   | N |                 |
| Transportation |     |          |           |   | G |                 |
|                |     |          |           |   | / |                 |
| Washington, DC |     |          |           |   | M |                 |
| 20590          |     |          |           |   | O |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | I |                 |
|                |     |          |           |   | T |                 |
|                |     |          |           |   | O |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | I |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | G |                 |
|                |     |          |           |   | \ |                 |
|                |     |          |           |   | A |                 |
|                |     |          |           |   | G |                 |
|                |     |          |           |   | E |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | C |                 |
|                |     |          |           |   | Y |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | E |                 |
|                |     |          |           |   | P |                 |
|                |     |          |           |   | O |                 |
|                |     |          |           |   | R |                 |
|                |     |          |           |   | T |                 |
|                |     |          |           |   | N |                 |
|                |     |          |           |   | U |                 |
|                |     |          |           |   | M |                 |
|                |     |          |           |   | B |                 |
|                |     |          |           |   | E |                 |
|                |     |          |           |   | R |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 11\.           |     |          |           |   |   |                 |
| SUPPLEMENTARY  |     |          |           |   |   |                 |
| NOTES          |     |          |           |   |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 12a.           |     |          |           |   | 1 |                 |
| DISTRIBUTIO    |     |          |           |   | 2 |                 |
| N/AVAILABILITY |     |          |           |   | b |                 |
| STATEMENT      |     |          |           |   | . |                 |
|                |     |          |           |   | D |                 |
| **Available    |     |          |           |   | I |                 |
| From**:        |     |          |           |   | S |                 |
| National       |     |          |           |   | T |                 |
| Technical      |     |          |           |   | R |                 |
| Information    |     |          |           |   | I |                 |
| Service/NTIS,  |     |          |           |   | B |                 |
| Springfield,   |     |          |           |   | U |                 |
| Virginia,      |     |          |           |   | T |                 |
| 22161. Phone   |     |          |           |   | I |                 |
| 703.605.6000,  |     |          |           |   | O |                 |
| Fax            |     |          |           |   | N |                 |
| 703.605.6900,  |     |          |           |   | C |                 |
| Email          |     |          |           |   | O |                 |
| \[orders@ntis. |     |          |           |   | D |                 |
| fedworld.gov\] |     |          |           |   | E |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 13\. ABSTRACT  |     |          |           |   |   |                 |
| (Maximum 200   |     |          |           |   |   |                 |
| words)         |     |          |           |   |   |                 |
|                |     |          |           |   |   |                 |
| This reference |     |          |           |   |   |                 |
| document was   |     |          |           |   |   |                 |
| prepared for   |     |          |           |   |   |                 |
| the Office of  |     |          |           |   |   |                 |
| Research,      |     |          |           |   |   |                 |
| Demonstration  |     |          |           |   |   |                 |
| and Innovation |     |          |           |   |   |                 |
| of the Federal |     |          |           |   |   |                 |
| Transit        |     |          |           |   |   |                 |
| Administration |     |          |           |   |   |                 |
| (FTA). The     |     |          |           |   |   |                 |
| objectives of  |     |          |           |   |   |                 |
| the study      |     |          |           |   |   |                 |
| include        |     |          |           |   |   |                 |
| developing a   |     |          |           |   |   |                 |
| methodology    |     |          |           |   |   |                 |
| for            |     |          |           |   |   |                 |
| determining    |     |          |           |   |   |                 |
| the return on  |     |          |           |   |   |                 |
| investment of  |     |          |           |   |   |                 |
| real-time      |     |          |           |   |   |                 |
| information    |     |          |           |   |   |                 |
| systems for    |     |          |           |   |   |                 |
| bus services,  |     |          |           |   |   |                 |
| examining the  |     |          |           |   |   |                 |
| relevant       |     |          |           |   |   |                 |
| technologies,  |     |          |           |   |   |                 |
| system         |     |          |           |   |   |                 |
| boundaries,    |     |          |           |   |   |                 |
| unit costs and |     |          |           |   |   |                 |
| benefits of    |     |          |           |   |   |                 |
| such systems,  |     |          |           |   |   |                 |
| and then       |     |          |           |   |   |                 |
| presenting     |     |          |           |   |   |                 |
| them within a  |     |          |           |   |   |                 |
| benefit-cost   |     |          |           |   |   |                 |
| evaluation     |     |          |           |   |   |                 |
| structure.     |     |          |           |   |   |                 |
| This study     |     |          |           |   |   |                 |
| includes the   |     |          |           |   |   |                 |
| input of an    |     |          |           |   |   |                 |
| Expert Panel   |     |          |           |   |   |                 |
| Workshop to    |     |          |           |   |   |                 |
| refine the     |     |          |           |   |   |                 |
| individual     |     |          |           |   |   |                 |
| cost and       |     |          |           |   |   |                 |
| benefit        |     |          |           |   |   |                 |
| elements, and  |     |          |           |   |   |                 |
| to obtain      |     |          |           |   |   |                 |
| information    |     |          |           |   |   |                 |
| from transit   |     |          |           |   |   |                 |
| agency         |     |          |           |   |   |                 |
| r              |     |          |           |   |   |                 |
| epresentatives |     |          |           |   |   |                 |
| on how transit |     |          |           |   |   |                 |
| agencies       |     |          |           |   |   |                 |
| measure or     |     |          |           |   |   |                 |
| would measure  |     |          |           |   |   |                 |
| a return on    |     |          |           |   |   |                 |
| investment of  |     |          |           |   |   |                 |
| these systems. |     |          |           |   |   |                 |
| Two approaches |     |          |           |   |   |                 |
| are examined   |     |          |           |   |   |                 |
| for            |     |          |           |   |   |                 |
| calculating    |     |          |           |   |   |                 |
| the            |     |          |           |   |   |                 |
| costs---direct |     |          |           |   |   |                 |
| costs, which   |     |          |           |   |   |                 |
| would only     |     |          |           |   |   |                 |
| give a model   |     |          |           |   |   |                 |
| useful for     |     |          |           |   |   |                 |
| incremental    |     |          |           |   |   |                 |
| cost           |     |          |           |   |   |                 |
| calculations,  |     |          |           |   |   |                 |
| and a          |     |          |           |   |   |                 |
| f              |     |          |           |   |   |                 |
| ully-allocated |     |          |           |   |   |                 |
| approach,      |     |          |           |   |   |                 |
| which would be |     |          |           |   |   |                 |
| more useful    |     |          |           |   |   |                 |
| for modeling   |     |          |           |   |   |                 |
| larger         |     |          |           |   |   |                 |
| deployments.   |     |          |           |   |   |                 |
| This           |     |          |           |   |   |                 |
| evaluation     |     |          |           |   |   |                 |
| also applies   |     |          |           |   |   |                 |
| the            |     |          |           |   |   |                 |
| return         |     |          |           |   |   |                 |
| -on-investment |     |          |           |   |   |                 |
| study on an    |     |          |           |   |   |                 |
| operational    |     |          |           |   |   |                 |
| system using   |     |          |           |   |   |                 |
| the evaluation |     |          |           |   |   |                 |
| elements and   |     |          |           |   |   |                 |
| methodology    |     |          |           |   |   |                 |
| developed for  |     |          |           |   |   |                 |
| the project.   |     |          |           |   |   |                 |
| This           |     |          |           |   |   |                 |
| application of |     |          |           |   |   |                 |
| the            |     |          |           |   |   |                 |
| benefit-cost   |     |          |           |   |   |                 |
| methodology    |     |          |           |   |   |                 |
| served as the  |     |          |           |   |   |                 |
| initial        |     |          |           |   |   |                 |
| validation of  |     |          |           |   |   |                 |
| the            |     |          |           |   |   |                 |
| methodology    |     |          |           |   |   |                 |
| and its        |     |          |           |   |   |                 |
| elements. The  |     |          |           |   |   |                 |
| demonstration  |     |          |           |   |   |                 |
| concludes with |     |          |           |   |   |                 |
| an outline of  |     |          |           |   |   |                 |
| the types of   |     |          |           |   |   |                 |
| information    |     |          |           |   |   |                 |
| required to    |     |          |           |   |   |                 |
| conduct a      |     |          |           |   |   |                 |
| benefit-cost   |     |          |           |   |   |                 |
| analysis of a  |     |          |           |   |   |                 |
| real-time      |     |          |           |   |   |                 |
| information    |     |          |           |   |   |                 |
| system.        |     |          |           |   |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
| 14\. SUBJECT   |     |          |           |   |   | 15\. NUMBER OF  |
| TERMS          |     |          |           |   |   | PAGES           |
|                |     |          |           |   |   |                 |
| Real-Time      |     |          |           |   |   | 68              |
| Information    |     |          |           |   |   |                 |
| Systems for    |     |          |           |   |   |                 |
| Bus Service,   |     |          |           |   |   |                 |
| Return on      |     |          |           |   |   |                 |
| Investment,    |     |          |           |   |   |                 |
| Benefit-Cost,  |     |          |           |   |   |                 |
| Transit and    |     |          |           |   |   |                 |
| Passenger      |     |          |           |   |   |                 |
| Information.   |     |          |           |   |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+
|                |     |          |           |   |   | 16\. PRICE CODE |
+----------------+-----+----------+-----------+---+---+-----------------+
| 17\. SECURITY  | 1   |          | 19\.      |   |   | 20\. LIMITATION |
| C              | 8\. |          | SECURITY  |   |   | OF ABSTRACT     |
| LASSIFICATION\ | SE  |          | CLASSI    |   |   |                 |
| OF REPORT      | CUR |          | FICATION\ |   |   |                 |
|                | ITY |          | OF        |   |   |                 |
| Unclassified   | CLA |          | ABSTRACT  |   |   |                 |
|                | SSI |          |           |   |   |                 |
|                | FIC |          | Unc       |   |   |                 |
|                | ATI |          | lassified |   |   |                 |
|                | ON\ |          |           |   |   |                 |
|                | OF  |          |           |   |   |                 |
|                | T   |          |           |   |   |                 |
|                | HIS |          |           |   |   |                 |
|                | P   |          |           |   |   |                 |
|                | AGE |          |           |   |   |                 |
|                |     |          |           |   |   |                 |
|                | Unc |          |           |   |   |                 |
|                | las |          |           |   |   |                 |
|                | sif |          |           |   |   |                 |
|                | ied |          |           |   |   |                 |
+----------------+-----+----------+-----------+---+---+-----------------+

NSN 7540-01-280-5500 Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std. 239-18298-102

Preface

The information developed and presented in this document was prepared
for the Federal Transit Administration (FTA) by a project team from Booz
Allen Hamilton. The project team included Donald Schneck, Rick Laver,
Georges Darido, Laura Cham and David Jackson. The project was contracted
through the Architecture and Engineering Contract with the Office of
Research, Demonstration and Innovation.

The project was managed through the FTA Office of Research,
Demonstration and Innovation, and its Office of Mobility Innovation. The
FTA project manager was Charlene Wilder. Overall guidance was provided
by Walt Kulyk, Director of the Office of Mobility Innovation. In
addition, an FTA technical oversight panel included Paul Marx of the
Office of Policy and Budget, Eric Pihl of the Office of Planning and
Environment, and Brian Cronin, Aletha Goodine and Sebastien Renaud of
the Office of Research, Demonstration and Innovation. The panel offered
guidance in the development of the methodology, the conduct of the
expert panel workshop and comments on the results. These contributions
were important to the direction and pertinence of the results, and the
project team would like to thank the FTA staff and panel for their
assistance.

The project team would also like to thank Tri-County Metropolitan
Transportation District of Oregon (TriMet). TriMet kindly offered their
support and information to the application of the benefit-cost
methodology developed as part of this study. David Crout of TriMet staff
provided detailed cost and benefit data to support the application of
the benefit-cost methodology. TriMet's success with the implementation
of their real-time bus arrival, passenger information system, among
other intelligent information systems, provided the actual data and
experience to demonstrate the methodology on an operational system.

The project team would also like to thank the expert panel members who
contributed insight and guidance to the development of the methodology.
These members included:

![](media/image5.wmf){width="6.879166666666666in"
height="4.465972222222222in"}

TABLE OF CONTENTS

[EXECUTIVE SUMMARY 1](#__RefHeading___Toc138656586)

[Real-time Bus Arrival Information Systems
1](#__RefHeading___Toc138656587)

[Study Objectives 1](#__RefHeading___Toc138656588)

[Expert Panel 2](#__RefHeading___Toc138656589)

[Return-on-Investment Methodology 2](#__RefHeading___Toc138656590)

[Application of the Proposed Methodology
3](#__RefHeading___Toc138656591)

[Future Applications and Enhancements 3](#__RefHeading___Toc138656592)

[1.0 INTRODUCTION 5](#__RefHeading___Toc138656593)

[1.1 Study Objectives 5](#__RefHeading___Toc138656594)

[1.2 Report Organization 5](#__RefHeading___Toc138656595)

[2.0 BACKGROUND 6](#__RefHeading___Toc138656596)

[2.1 Project Overview 6](#__RefHeading___Toc138656597)

[2.2 Understanding of the Problem 8](#__RefHeading___Toc138656598)

[2.3 Business Case for Systems Investments
8](#__RefHeading___Toc138656599)

[2.4 Real-time Bus Arrival Information Systems Studies
9](#__RefHeading___Toc138656600)

[3.0 PROJECT APPROACH 11](#__RefHeading___Toc138656601)

[3.1 Overview of the Study Process 11](#__RefHeading___Toc138656602)

[3.2 Return on Investment 12](#__RefHeading___Toc138656603)

[3.3 Kickoff Meeting 14](#__RefHeading___Toc138656604)

[3.4 Expert Panel Workshop 14](#__RefHeading___Toc138656605)

[3.5 Benefit-cost Methodology and Application
15](#__RefHeading___Toc138656606)

[4.0 EXPERT PANEL WORKSHOP 16](#__RefHeading___Toc138656607)

[4.1 Introduction 16](#__RefHeading___Toc138656608)

[4.2 Workshop Synopsis 16](#__RefHeading___Toc138656609)

[4.3 Technologies Utilized 17](#__RefHeading___Toc138656610)

[4.4 Benefits 17](#__RefHeading___Toc138656611)

[4.5 Implementation 19](#__RefHeading___Toc138656612)

[4.6 Data Quality 20](#__RefHeading___Toc138656613)

[4.7 Return on Investment Analysis 20](#__RefHeading___Toc138656614)

[4.8 Summary of Surveys 21](#__RefHeading___Toc138656615)

[5.0 RETURN ON INVESTMENT: THEORY AND APPLICATION
25](#__RefHeading___Toc138656616)

[5.1 ROI Measures and Public Transit Investments
25](#__RefHeading___Toc138656617)

[5.2 Application of Benefit-Cost Analysis to Real-Time Information
Systems 28](#__RefHeading___Toc138656618)

[5.3 Cost Effectiveness Measures 28](#__RefHeading___Toc138656619)

[5.4 Identification of Investment Costs and Benefits
30](#__RefHeading___Toc138656620)

[5.5 System Boundaries 31](#__RefHeading___Toc138656621)

[5.6 Hierarchy of Investment Benefits 32](#__RefHeading___Toc138656622)

[5.7 Customer-Facing Technology Benefits
34](#__RefHeading___Toc138656623)

[5.8 Enabling Technology Benefits 35](#__RefHeading___Toc138656624)

[6.0 DEMONSTRATION OF BENEFIT-COST ANALYSIS PROCESS TRANSIT TRACKER
37](#__RefHeading___Toc138656625)

[6.1 Introduction 37](#__RefHeading___Toc138656626)

[6.2 TriMet's Transit Tracker System 38](#__RefHeading___Toc138656627)

[6.3 Evaluation Approach 39](#__RefHeading___Toc138656628)

[6.4 Transit Tracker Capital and Operating Costs
43](#__RefHeading___Toc138656629)

[6.5 Estimated Number of Uses of Transit Tracker
45](#__RefHeading___Toc138656630)

[6.6 Case Evaluations 48](#__RefHeading___Toc138656631)

[6.6 Conclusion 54](#__RefHeading___Toc138656632)

[6.7 Future Applications and Enhancements
54](#__RefHeading___Toc138656633)

[BIBLIOGRAPHY 55](#__RefHeading___Toc138656634)

[APPENDIX A: Agenda -- August 9, 2005 56](#__RefHeading___Toc138656635)

[APPENDIX B: List of Participants to August 9, 2005 Expert Panel
Workshop 57](#__RefHeading___Toc138656636)

[APPENDIX C: Survey Description 58](#__RefHeading___Toc138656637)

[]{#__RefHeading___Toc138656586 .anchor}EXECUTIVE SUMMARY

This study was developed to help transit agencies with the development
and implementation of Intelligent Transportation Systems (ITS), in
general, and Real-time Passenger Information Systems in particular. The
focus of the study effort is the return on investment (ROI) in these
passenger information systems and the methodology used to apply this
evaluation approach.

[]{#__RefHeading___Toc138656587 .anchor}Real-time Bus Arrival
Information Systems

Intelligent Transportation Systems (ITS) have been the focus of efforts
to improve the effectiveness of transportation services and allow them
to become more customer friendly. Real-time Bus Arrival Information
Systems are one aspect of these ITS systems that focus upon real-time
bus operations information and distributes that information to the
public in an effort to reduce passenger wait times.

These real-time bus information systems have been implemented to
facilitate transit usage through both perceived and actual reductions in
passenger waiting time. Access to this information before beginning the
trip can help to reduce the wait time. Information available to the
traveler underway can help to reduce the perceived wait time.

[]{#__RefHeading___Toc138656588 .anchor}Study Objectives

The objectives of the study were oriented toward the development of a
methodology for determining the return on investment of real-time
information systems for bus services. This includes examining the
relevant technologies, system boundaries, unit costs and benefits of
such systems, and then presenting them within a benefit-cost evaluation
structure. The study objectives included the following:

-   Develop a generic methodology for determining the return on
    investment of real-time bus arrival information systems

-   Investigate and collect unit costs, impacts, and
    return-on-investment information

-   Present the proposed methodology to an expert panel

-   Perform a return-on-investment study using the methodology developed

-   Test the methodology on an expansion of an existing system in a
    potential future phase of the project

[]{#__RefHeading___Toc138656589 .anchor}Expert Panel

The project team organized and conducted the Expert Panel Workshop to
refine the individual cost and benefit elements, and to provide feedback
on the proposed methodology for performing the return-on-investment
studies of real-time bus arrival information systems. The purpose of the
expert panel was to obtain information from transit agency
representatives on how transit agencies measure or would measure a
return on investment of these systems. Comparable input was also
garnered from automatic vehicle location (AVL)/real-time transit
information system vendors. The role of the expert panel was to:

-   Validate the boundaries of the relevant systems and technologies

-   Provide input on the proposed benefit-cost analysis methodology

-   Identify and help quantify all relevant costs and benefits

-   Identify additional data sources

-   Provide insight on barriers to implementation

To facilitate and provide structure for the workshop, the project team
identified and presented draft return-on-investment study elements and a
draft methodology. The expert panel discussed the draft elements and
methodology proposed by the Booz Allen project team and suggested
revisions to the process to emphasize the benefit-cost approach. The
panel reached a consensus on the benefit-cost elements and the
methodology.

[]{#__RefHeading___Toc138656590 .anchor}Return-on-Investment Methodology

The heart of the return-on-investment evaluation was a detailed
benefit-cost analysis. When used to evaluate new technologies,
traditional benefit-cost analyses compare the discounted streams of
costs and benefits associated with the proposed technology---including
costs and benefits to individual riders and operating agencies, and to
society in general. Implementation of the new technology is viewed as
desirable---either to the individuals or to society as a whole---when
the benefits of implementation exceed the costs (i.e., the ratio of
discounted benefits over discounted costs exceeds one). While
traditional benefit-cost analyses are generally limited to costs and
benefits that are quantifiable in monetary (dollar) terms, practitioners
have developed several techniques to include both and qualitative and
non-monetary quantitative factors as well.

Two approaches were examined for calculating the costs---direct costs
only and both direct and indirect costs associated with the real-time
information systems. Using the direct costs only would give a model
useful for incremental cost calculations. Using the fully-allocated
model would be more useful for modeling larger deployments. It was
agreed that the fully-allocated cost model was the preferred approach
and that it would be best to show both methods as appropriate.

[]{#__RefHeading___Toc138656591 .anchor}Application of the Proposed
Methodology

With concurrence from the Federal Transit Administration (FTA) and the
results from the Expert Panel Workshop, the project team contacted
selected transit agencies to apply the benefit-cost methodology to a
particular real-time bus arrival system investment decision. The request
focused on availability of unit costs, benefits, impacts, and
return-on-investment information on real-time bus arrival information
systems. This information and the recent system implementation were
found available at TriMet in Portland, Oregon. The project team worked
with representatives of this agency to apply the return-on-investment
study on an operational system using the evaluation elements and
methodology developed for the project. This application of the
benefit-cost methodology served as the initial validation of the
methodology and its elements.

This brief demonstration has outlined the types of information required
to conduct a benefit-cost analysis of a real-time information system,
using TriMet's Transit Tracker system as a test case. In addition to
highlighting the information needs associated with this type of
analysis, this demonstration has also outlined the circumstances
required to attain a positive net benefit for the Transit Tracker
system. Using fairly conservative assumptions regarding informed trip
volumes, reductions in wait time and reduction in the cost of wait-time
uncertainty, it was shown that Transit Tracker very likely achieves
strong, positive net (social) benefits. The completion of a more
conclusive assessment of Transit Tracker or any other real-time
information system in the future will require the collection of specific
use data as required to replace these assumptions with robust parameter
estimates (e.g., estimates of the number of trips for which a real-time
information system is used, the average time savings for each use, etc.)

#  {#section .unnumbered}

[]{#__RefHeading___Toc138656592 .anchor}Future Applications and
Enhancements

The results from this development of the return-on-investment approach
for real-time bus arrival passenger information systems may be applied
in a potential, future field test and return-on-investment study. As
existing systems become more widely implemented and accepted by the
transit rider, the benefits of these systems can be more clearly
demonstrated. Options include those transit systems with existing
passenger information systems such as:

-   TriMet

-   Los Angeles County MTA

-   King County Metro

-   San Francisco Muni

-   Pace (suburban Chicago)

-   Denver RTD

-   Fairfax CUE

-   Cape Cod Regional Transit Authority

-   AC Transit (Oakland, CA)

-   Portland Streetcar

This process can also be applied with other system investments within
the overall Intelligent Transportation Systems (ITS) realm. The FTA will
determine if the subsequent field test and return-on-investment study
are needed.

[]{#__RefHeading___Toc138656593 .anchor}1.0 INTRODUCTION

This research study was guided by the Federal Transit Administration
(FTA) Office of Research, Demonstration and Innovation. Funding was
provided through the Joint Program Office of the Federal Highway
Administration (FHWA). This study was developed to help transit agencies
with the development and implementation of Intelligent Transportation
Systems in general, and Real-time Passenger Information Systems in
particular. The focus of the study effort is the return on investment
(ROI) in these passenger information systems.

[]{#__RefHeading___Toc138656594 .anchor}1.1 Study Objectives

The objectives of the study were oriented toward the development of a
methodology for determining the return on investment of real-time
information systems for bus services. This includes examining the
relevant technologies, system boundaries, unit costs and benefits of
such systems, and then presenting them within a benefit-cost evaluation
structure. The study objectives included the following:

-   Develop a generic methodology for determining the return on
    investment of real-time bus arrival information systems

-   Investigate and collect unit costs, impacts, and
    return-on-investment information

-   Present the proposed methodology to an expert panel

-   Perform a return-on-investment study using the methodology developed

-   Test the methodology on an expansion of an existing system in a
    potential future phase of the project

[]{#__RefHeading___Toc138656595 .anchor}1.2 Report Organization

In accordance with the proposed framework outlined in the project work
plan, this study is organized into the following sections:

1.0 Introduction

2.0 Background

3.0 Project Approach

4.0 Expert Panel

5.0 Return on Investment Methodology

6.0 Sample Application

This presentation of the study results reflects the process undertaken
in the study, the approach required in its implementation and the
results outlined for each deliverable.

[]{#__RefHeading___Toc138656596 .anchor}2.0 BACKGROUND

Intelligent Transportation Systems (ITS) have been the focus of efforts
to improve the effectiveness of transportation services and allow them
to become more customer friendly. Real-time Bus Arrival Information
Systems are one aspect of these ITS systems that focus upon real-time
bus operations information and distributes that information to the
public in an effort to reduce passenger wait times.

These real-time bus information systems have been implemented to
facilitate transit usage through both perceived and actual reductions in
passenger waiting time. Access to this information before beginning the
trip can help to reduce the wait time. Information available to the
traveler underway can help to reduce the perceived wait time. This
Return-on-Investment (ROI) Study has been developed in accordance with
the strategic goals of the Federal Transit Administration (FTA) for
measuring cost-effectiveness and improving financial performance of
transit investments. It provides an improved understanding of the costs
and benefits of these systems and the means to estimate these impacts
within the decision-making process of the investment question.

[]{#__RefHeading___Toc138656597 .anchor}2.1 Project Overview

One such ITS investment that is becoming more widely implemented is
real-time bus arrival information system. The development of real-time
bus arrival systems has been accomplished through several alternative
technologies and differing technical approaches. Some of these interact
directly with the vehicle location systems and utilize similar
satellite-based communications networks to determine bus arrival times.
Others utilize cellular-based communication to identify vehicle location
and from that estimate the bus arrival times to upcoming destinations.
Both of these technologies have been demonstrated successfully. State of
the practice in these systems has been well documented, and the
alternative approaches are well understood.

The critical technical issues in real-time bus arrival systems are the
collection, communication, display, and then dissemination of the
real-time bus arrival information. This implementation process has been
examined in recent research and has been achieved successfully at
several agencies. However, the hypothesis has been posed that system
deployments around the country still fail, are under-utilized, or do not
achieve the desired outcome because of ineffective planning or lack of
information to support the investment decisions for these systems.

Although technical issues are critical to the implementation and
utilization of a real-time bus arrival system, the most important issues
at the decision point in their deployment are the justification of the
system and then the implementation of the system in a way that achieves
maximum customer benefits from its use. Dissemination of traveler and
vehicle information through a mechanism that is useful to current and
potential bus riders is essential in order to reap the benefits from the
capital investment and ongoing maintenance costs for the system. This
return-on-investment approach to the development, evaluation and
implementation of real-time passenger information systems is the focus
of this research study.

The motivation for this study is based on the extensive deployments that
occurred previously and the significant slowing of the deployments in
more recent years.

-   Deployment of real-time bus arrival information systems in the
    United States during the 1990s grew significantly. As of 2000:

```{=html}
<!-- -->
```
-   88 transit agencies had operational AVL systems

-   142 were planning AVL systems

-   291 had operational automated transit information

-   48 were planning automated transit information

```{=html}
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```
-   Future deployment of these systems may be hindered by:

    -   Uncertainties in the utilization and return of such investments

    -   Lack of a consistent benefit-cost methodology for investment
        decision

This project was developed to help answer this question of future
deployments.

Continued development and implementation of real-time bus arrival
systems may be hindered by lack of a clear justification of the
benefits. Additionally, there is no systematic utilization of the
real-time bus arrival information to achieve the objectives of increased
customer satisfaction, and improved service and transit visibility. The
highest benefits, however, may be achieved from increased transit
ridership. This includes more frequent travel by current riders and the
additional travel of new riders.

The FTA has noted that real-time transit information systems have many
perceived benefits, including the following:

-   Maintenance of or increase in transit ridership

-   Improvement of customer service

-   Increase in customer satisfaction and convenience

-   Improvement of transit visibility

-   Provision of critical information during emergencies

These benefits and their measurement are the focus of the benefit-cost
approach. The quantitative measurement of these benefits and the values
of those benefits are critical to the success of this process and the
demonstration of the real-time bus arrival information systems.

[]{#__RefHeading___Toc138656598 .anchor}2.2 Understanding of the Problem

There are issues critical to the implementation of real-time bus arrival
systems and there are issues critical to its utilization, but the most
important issues are the justification of the system(s) and then the
implementation of the system to achieve the customer benefits from its
use. Dissemination of the resulting traveler and vehicle information in
a useful mechanism to current and potential bus riders is essential in
reaping the benefits from the system capital investment and ongoing
maintenance.

One potential issue that may stand in the way of continued development
and implementation of these real-time bus arrival systems is the clear
quantitative measurement of the costs and benefits and justification of
these systems investments. The systematic utilization of the information
to achieve the objectives of increased customer satisfaction, ridership
increases, travel time savings and service and transit visibility are
the keys to their successful implementation. However, the highest
benefits are likely achieved from travel time savings and potential
increases in transit ridership from more reliable service and greater
passenger visibility into this real-time bus arrival information. The
challenge lies in collecting data that provide a reliable measure of
each of these benefits.

[]{#__RefHeading___Toc138656599 .anchor}2.3 Business Case for Systems
Investments

The heart of any business case is the benefit-cost analysis. When used
to evaluate new technologies, traditional benefit-cost analyses compares
the discounted streams of costs and benefits associated with the
proposed technology --- including costs and benefits to individual
riders and operating agencies, and to society in general. Implementation
of the new technology is viewed as desirable --- either to the
individuals or to society as a whole --- when the benefits of
implementation exceed the costs (i.e., the ratio of discounted benefits
over discounted costs exceeds one). While traditional benefit-cost
analyses are generally limited to costs and benefits that are
quantifiable in monetary (dollar) terms, practitioners have developed
several techniques to include both qualitative and non-monetary
quantitative factors, as well as the more traditional monetary
quantitative measures. This process considers both types.

Completion of a comprehensive benefit-cost analysis requires the
identification of all direct and indirect costs and benefits associated
with the proposed real-time bus arrival system investment. In general,
the full range of costs and benefits to include in the analysis will
expand as the number of stakeholders considered in the analysis
increases. For example, a benefit-cost analysis for an individual agency
may not consider costs and benefits to other regional beneficiaries such
as the riders and other users of the bus arrival information. Similarly,
an industry level benefit-cost analysis may not consider broader
benefits to society as a whole (e.g., vehicle emissions from the former
drivers). Hence, it is important to consider all stakeholders at the
start to insure the more comprehensive identification of costs and
benefits. Finally, while it is critical that the listing of costs and
benefits be comprehensive, it is equally important to avoid double
counting (counting the same cost or benefit twice) and transfers (where
a benefit to one stakeholder becomes a cost to another stakeholder, with
no net benefit to society). The proposed benefit-cost approach fulfills
the Federal Office of Management and Budget Circular A-4 requirements
for measuring benefits and costs, and supports the wider implementation
of these systems in the future.

The deployment of real-time traveler information systems for transit is
becoming more prevalent. The advent of automatic vehicle location (AVL)
systems not only has provided the transit industry with tools to monitor
and control operations, but the opportunity to provide customers with
real-time information. Real-time traveler information systems for
transit, also referred to as real-time transit information systems,
display information in different ways using a variety of dissemination
devices. Many applications use a countdown to arrival of the next
transit vehicle (e.g., next bus in 5 minutes). Some systems provide the
estimated time of day (e.g., 3:45 PM) for the arrival of the next
transit vehicle. Other systems provide the geographic location of
vehicles on a route map. Dissemination media include dynamic message
signs (DMS), video monitors, and kiosks at transit stops and stations,
the Internet, telephones, and personal digital assistant (PDA) devices.

[]{#__RefHeading___Toc138656600 .anchor}2.4 Real-time Bus Arrival
Information Systems Studies

Transit agencies have implemented a significant number of real-time
transit information systems, although, prior to 2002, only a limited
amount of information about them was available. In 2002, two research
studies were conducted to obtain useful information on these systems.
Reports from these studies include the following:

-   *Guidance for Developing and Deploying Real-time Traveler
    Information for Transit*, developed by Battelle for the Federal
    Transit Administration (FTA) and United States Department of
    Transportation (U.S. DOT) Intelligent Transportation Systems (ITS)
    Joint Program Office (JPO), April 30, 2003, U.S. DOT \#
    FTA-OH-26-7017-2003.1

-   *TCRP Synthesis 48: Real-time Bus Arrival Information Systems*,
    Transit Cooperative Research Program (TCRP), Transportation Research
    Board (TRB), 2003

The first document identifies the issues and challenges of planning,
implementing, operating, and maintaining real-time transit information
systems, and identifies recommended practices. The second document is a
synthesis of the state of the practice in real-time bus arrival systems.

Few evaluations of these systems have occurred or have been documented
publicly. However, Tri-County Metropolitan Transportation District of
Oregon (TriMet) performed a small in-house assessment of its Transit
Tracker system. This assessment was followed by a national evaluation
sponsored by the U.S. DOT ITS Joint Program Office as a part of the
National Evaluation Program. In both of these evaluations, a
quantitative analysis of user perceptions was conducted based on survey
data. The evaluations provide quantitative results of the system's
operational performance and impacts based on the analysis of subjective
data. The evaluations do not provide quantitative results of the
system's operational performance and impacts based on an analysis of
objective data, such as ridership numbers.

The justification by most transit agencies for implementing real-time
transit information systems is to improve customer satisfaction.
Information on the general qualitative impacts of these systems is
available; however, the quantitative impacts of these systems are
lacking. Therefore, a need existed to develop a quantitative structure
to estimate the benefits and costs of these systems, to assess the value
of these benefits and costs, and to determine the return on investment.

[]{#__RefHeading___Toc138656601 .anchor}3.0 PROJECT APPROACH

The purpose of this project was to conduct a return-on-investment study
of bus real-time traveler information systems, also referred to as
real-time bus arrival information systems. The study was limited to
real-time traveler information systems for buses (as opposed to bus and
passenger rail) to establish the process within a manageable scope and
project size. This section describes the study approach applied to
develop this quantitative approach to the benefit-cost structure.

A major goal of the Federal Transit Administration (FTA) has been to
increase transit ridership by two percent annually. It is hypothesized
that real-time bus arrival information systems may help transit agencies
increase ridership. This project technical approach measured the impacts
of these systems, including the impacts on transit ridership.

[]{#__RefHeading___Toc138656602 .anchor}3.1 Overview of the Study
Process

The overall goal of the project was to develop generic benefit-cost
elements and a generic methodology (set of criteria) for evaluating the
return on investment (ROI) of real-time bus arrival information systems,
and to demonstrate a benefit-cost analysis (calculate the return on
investment of an operational real-time bus arrival information systems).
Successful implementation of this project was intended to assist transit
agencies in assessing the return on investment of real-time bus arrival
information systems, shed light on the benefits versus the costs of
these systems, and provide objective justification for implementing
real-time transit information systems or for spending funds on other
higher priority capital projects. Since the process application results
were favorable (i.e., benefits exceed costs), the project results and
the methodology may lead to a more widespread deployment of these
systems.

The project was initiated with the development of an outreach effort.
This involved the conduct of an expert panel to identify
return-on-investment evaluation elements and suggest a methodology for
the benefit-cost analysis. The project team convened an expert panel
representing transit agencies that have operating real-time bus arrival
information systems and automatic vehicle location (AVL)/real-time
transit information systems, as well as vendors of these systems. The
panel session was organized to provide feedback to the study team on the
proposed process, and to refine the process to reflect investment
planning and implementation operational conditions.

Evaluation process elements included items such as:

-   Benefits

-   Costs

-   Measures of effectiveness

-   Data elements

-   Data sources.

Together the project team and the expert panel determined the preferred
approach to conduct a return-on-investment study of real-time bus
arrival information systems. This approach is based on the perspective
of and input from transit agencies and AVL/real-time transit information
system vendors.

A survey was conducted with these selected transit agencies with
operational systems and vendors to investigate the unit costs of these
systems and to identify any studies that the transit agencies may have
performed on these systems where system impacts or the return on
investment was measured. Data availability was provided through the
survey, but it was limited because virtually all of the systems had not
completed a benefit-cost analysis of the system investment. The
benefit-cost methodology developed for the study was applied and tested
on the investment in real-time bus arrival systems at TriMet in
Portland, Oregon. This application of the benefit-cost process served as
the demonstration of the study methodology and its elements.

[]{#__RefHeading___Toc138656603 .anchor}3.2 Return on Investment

The heart of the return-on-investment evaluation was a detailed
benefit-cost analysis. When used to evaluate new technologies,
traditional benefit-cost analyses compare the discounted streams of
costs and benefits associated with the proposed technology---including
costs and benefits to individual riders and operating agencies, and to
society in general. Implementation of the new technology is viewed as
desirable---either to the individuals or to society as a whole---when
the benefits of implementation exceed the costs (i.e., the ratio of
discounted benefits over discounted costs exceeds one). While
traditional benefit-cost analyses are generally limited to costs and
benefits that are quantifiable in monetary (dollar) terms, practitioners
have developed several techniques to include both and qualitative and
non-monetary quantitative factors as well.

Two approaches were examined for calculating the costs---direct costs
only and both direct and indirect costs associated with the real-time
information systems. Using the direct costs only would give a model
useful for incremental cost calculations. Using the fully-allocated
model would be more useful for modeling larger deployments. It was
agreed that the fully-allocated cost model was the preferred approach
and that it would be best to show both methods as appropriate.

The most appropriate methodology for quantifying the benefits was also
examined. Based on OMB Circular A-4, all of the traditional transit
benefits of increased ridership and reduced dwell time apply to this
evaluation, with the exception of increased fare revenue, which is a
transfer. On page 45 of the Circular, it recommends that benefits be
reported in three categories:

> I. Monetized
>
> II\. Quantifiable, but not monetized
>
> III\. Qualitative, but not quantifiable

The quantification process and the monetization of the costs and
benefits were guided by the methodology description included in the
following chapter. For example, using the list of potential benefits
included there, the following may be considered in the ROI in category
I:

-   New Riders:

    -   Transit Travel time savings

    -   Reduced auto costs

-   Existing Riders:

    -   In-vehicle transit travel time savings

    -   Out-of-vehicle transit travel time savings

-   Highway Users:

    -   Reduced congestion/delay from increased transit ridership

-   Agency/Operator Benefits:

    -   Reduced O&M costs

-   Social Benefits:

    -   Reduced highway maintenance/administration costs (may be
        negligible)

There are also potential benefits that are difficult to monetize
(category II) and may be very small:

-   Improved mobility for new riders

-   Reduced emissions - air

-   Reduced emissions - noise

-   Reduced accident rate

Finally, there are category III benefits that are difficult to quantify,
such as improved customer satisfaction through an increased sense of
security. The best way to gauge these benefits is through passenger
satisfaction or preference surveys.

[]{#__RefHeading___Toc138656604 .anchor}3.3 Kickoff Meeting

The project team attended an initial kickoff meeting with FTA officials
at the U.S. DOT headquarters in Washington, DC, to discuss the project
goals and expectations. The meeting focused on the project approach,
staffing levels, schedule, budget, tasks, deliverables, and travel. The
project manager and key staff assigned to the project attended the
kickoff meeting. The project team took notes and prepared meeting
minutes of the key points discussed. A clear understanding was gained of
the project challenges and the expectations for the results.

[]{#__RefHeading___Toc138656605 .anchor}3.4 Expert Panel Workshop

With direction and assistance from the FTA, the Booz Allen project team
established an expert panel of representatives from transit agencies
that have operating real-time bus arrival information systems, and
representatives from major AVL/real-time transit information system
vendors. The panel reflected a diverse set of transit agencies,
considering factors such as transit agency size and geographic location.
Also, the mix of transit agencies included those that have developed
systems in-house, developed systems with an AVL vendor, or have
purchased complete systems from a vendor.

The project team organized and conducted the Expert Panel Workshop to
refine the individual cost and benefit elements and to provide feedback
on the proposed methodology for performing the return-on-investment
studies of real-time bus arrival information systems. The purpose of the
expert panel was to obtain information from transit agency
representatives on how transit agencies measure or would measure a
return on investment of these systems. Comparable input was also
garnered from AVL/real-time transit information system vendors. To
facilitate and provide structure for the workshop, the project team
identified and presented draft return-on-investment study elements and a
draft methodology. The expert panel discussed the draft elements and
methodology proposed by the Booz Allen project team and suggested
revisions to the process to emphasize the benefit-cost approach. The
panel reached a consensus on the benefit-cost elements and the
methodology.

The project team also distributed a survey with the expert panel to
identify transit agencies that may have:

-   Unit cost information on real-time bus arrival information systems

-   Documented studies on real-time bus arrival information systems
    where system impacts or the return on investment was measured

-   Data available for the contractor to perform a return-on-investment
    study using the evaluation elements and methodology developed by the
    expert panel and contractor.

The results of the survey and the panel workshop are included within the
report.

[]{#__RefHeading___Toc138656606 .anchor}3.5 Benefit-cost Methodology and
Application

With direction from the FTA and the results from the expert panel
workshop, the project team contacted selected transit agencies to apply
the benefit-cost methodology to a particular real-time bus arrival
system investment decision. The request focused on availability of unit
costs, benefits, impacts, and return-on-investment information on
real-time bus arrival information systems. This information was found
available at TriMet in Portland, Oregon. The project team worked with
representatives of this agency to apply the return-on-investment study
on an operational system using the evaluation elements and methodology
developed for the project. This application of the benefit-cost
methodology served as the initial validation of the methodology and its
elements.

The following chapters of this final report present the results of the
expert panel meeting, the summary of the survey results, the
benefit-cost methodology and the application of that methodology on the
operational passenger information system at TriMet in Portland, Oregon.
Candidate sites for future field test and return-on-investment study of
real-time bus arrival information systems are also presented.

[]{#__RefHeading___Toc138656607 .anchor}4.0 EXPERT PANEL WORKSHOP

The first sections of this chapter include an introduction followed by a
synopsis of the major points, issues, and results of the workshop. The
next section is a summary of the survey responses and data received. The
concluding section is a brief discussion of the next steps and the
approach to refine the benefit-cost methodology.

[]{#__RefHeading___Toc138656608 .anchor}4.1 Introduction

A proposed methodology was presented to an expert panel consisting of
invited representatives from 11 transit agencies from across the country
with implementation experience, 4 system suppliers, the American Public
Transportation Association, Federal Highway Administration, Federal
Transit Administration and its consultant on this task, Booz Allen
Hamilton. The one-day workshop was held on August 9, 2005 at Montgomery
County's Public Safety Communications Center in Gaithersburg, Maryland.
The role of the expert panel was to:

-   Validate the boundaries of the relevant systems and technologies

-   Provide input on the proposed benefit-cost analysis methodology

-   Identify and help quantify all relevant costs and benefits

-   Identify additional data sources

-   Provide insight on barriers to implementation

Members of the expert panel were also asked to complete and return a
survey to document the individual real-time information system
implementation experiences.

[]{#__RefHeading___Toc138656609 .anchor}4.2 Workshop Synopsis

This section presents a synopsis of the key issues identified during the
Expert Panel Workshop. The tentative agenda for the meeting and the
complete list of attendees is included in **Appendices A** and **B** of
this report. The meeting attendees discussed the key issues related to
the delivery of real-time traveler information, which can be grouped
into five major topics:

-   Enabling technologies and customer-facing passenger information
    systems

-   Quantitative and qualitative benefits of these technologies

-   Implementation decisions and barriers

-   Data quality

-   Return-on-investment analysis

[]{#__RefHeading___Toc138656610 .anchor}4.3 Technologies Utilized

The expert panel recognized the essential contribution of a number of
vehicle location and network communications technologies that enable the
implementation of real-time passenger information. Current enabling
technologies include voice and data radios, Global Positioning Systems
(GPS), Galileo (new satellite location technology), loop-inductors,
signposts, repeaters and radio frequency identification devices (RFID).
These enabling technologies are complemented by supporting technologies,
such as software integration and servers. Customer-facing or passenger
information technologies include customer service centers, websites,
traveler information line (511 support), dynamic message signs (DMS),
information kiosks and voice annunciation systems. These passenger
information technologies were recognized as independent options to
provide different channels for each customer market segment, trip
purpose, income level, age and origin and destination locations.

Other issues related to the technologies involved the canyon effects of
GPS-based location determination equipment, polling rates, the
importance of open architecture, and the decision between dedicated and
public bandwidth, fiber optic and wireless computer networks, and
commercial or private technologies, which affect the quality,
availability and application of real-time information.

[]{#__RefHeading___Toc138656611 .anchor}4.4 Benefits

There was recognition by the expert panel of the importance to consider
both quantitative and qualitative benefits, including service operations
and customer satisfaction. While panel members felt there were clear
benefits to real-time information technologies, there was not general
agreement on what these benefits are and how they are quantified.
Benefits were also identified that result from enabling technologies and
customer facing information systems. There is also an overlap of the two
that makes it difficult to isolate the incremental benefits of real-time
information systems layered on enabling technologies. These are
summarized in **Table 4-1**.

**Table 4-1**

**Key Benefits of Real-Time Bus Arrival Information**

+----------------------+--------------------------+--------------------+
| **Supporting         | Overlapping              | Real-Time          |
| Technologies**       |                          | Information        |
+----------------------+--------------------------+--------------------+
| -   Improved on-time | -   Reduced passenger    | -   Use of         |
|     performance and  |     wait times and       |     passenger      |
|     schedule         |     better service       |     information    |
|     planning         |     reliability also     |     system to      |
|                      |     resulting in reduced |     disseminate    |
| -   Improved         |     safety/security      |     safety and     |
|     incident         |     risks                |     security       |
|     management and   |                          |     messages, and  |
|     response times   | -   Increased customer   |     next-bus       |
|                      |     satisfaction         |     arrival        |
|                      |                          |     information    |
+----------------------+--------------------------+--------------------+

Supporting technologies can improve on-time performance and schedule
planning through real-time operations management and development of
realistic schedules. The resulting, more reliable transportation can
help increase ridership by assisting passengers in keeping their work
and personal schedules. Real-time operations management also improves
failure management and incident response times, which helps restore a
system back to normal. These systems also provide litigation support for
accident investigations and customer complaint claims.

Passenger wait times are reduced by way of more reliable service and
passenger choices. Pre-trip information sources, such as customer
service centers, websites, traveler information line (e.g., 511
support), have a direct impact upon reduced passenger wait times and
help to increase choice travel. Although stop signage with next-arrival
information does not directly reduce wait times, since passengers have
to be at the stop to know this information, it reduces anxiety and may
provide a perceived benefit of less safety and security risk. Real-time
vehicle information helps operations management maintain buses on
schedule, which reduces service variability and increases passengers'
perception of performance. Real-time information is most valuable to
passengers in departure time decisions, i.e., what time to depart to a
stop, which requires access to pre-trip information. By knowing next-bus
arrival information, passengers may be able to make better use of their
time or seek alternate modes of transportation (e.g., if the wait time
is too long).

There is also the benefit of using passenger information systems for
public advisories, street closures, accidents or re-routing.
Communication systems, such as Transit Television Network (TTN), were
being used to disseminate safety and security messages to the riding
public.

Overall, there is improved fleet management and incident response times,
which helps restore the system back to normal. This may reduce the delay
incurred by the passengers, and increases customer satisfaction by way
of better service reliability, convenient traveler information and
improved customer services.

[]{#__RefHeading___Toc138656612 .anchor}4.5 Implementation

Several key issues in system implementation were identified by transit
agencies, which are summarized into four categories.

# 4.5.1 Customer-Driven Vs. Budget-Driven {#customer-driven-vs.-budget-driven .FTA-Heading-3}

The decision and level of implementation of real-time passenger
information systems can be driven by customer demand (or public
pressure) and quality of service improvements or by the available
budget. One transit agency stated that the decision to invest in
real-time system process was driven by the directive of senior staff,
board members and political stakeholders as a means of improving the
quality of customer service. Several additional panel members agreed
that this influence drove investment decisions more than internal
service improvement initiatives. This theme was agreed by virtually all
of the panel members, emphasizing top-down initiatives to invest in
these passenger information systems. As a consequence, the directive of
agency management to pursue real-time investments as an agency goal
often obviated the need for agency staff to perform their own, internal
return-on-investment studies for these investments. It was also noted
that implementation can be driven by customer expectations if similar
passenger information system exists on a different mode.

# 4.5.2 Barriers to Implementation {#barriers-to-implementation .FTA-Heading-3}

Barriers to implementation of the system and organizational changes
necessary for implementation identified by the panel included:

-   Security concerns with regards to the vulnerability of attacks
    knowing information about where the bus is and when it is arriving

-   Department and staff coordination, especially for regional agencies
    with multiple transit providers

-   Fleet maintenance and management, especially if only a subset of
    buses are equipped

-   Organizational changes in internal staff and management processes
    including the use of the new data and hiring new staff or training
    existing staff with the skills needed to coordinate integration and
    maintain the data.

# 4.5.3 Incremental or System-Wide Implementation  {#incremental-or-system-wide-implementation .FTA-Heading-3}

On the question of the scale of implementation, one transit agency
preferred the flexibility of phased/incremental implementation of system
components. Another agency emphasized the difficulties in incremental
installation based on the difficulties to maintain the fleet along the
same route. For another agency, the experience of implementation was
somewhere between, phasing system components on a garage-level basis.
Also discussed was the level of cooperation between the agency and the
supplier during implementation.

# 4.5.4 Marketing {#marketing .FTA-Heading-3}

To make riders aware of the new information sources, a number of
agencies mentioned the use of online resources (such as their website)
and other media to promote the new systems. Other agencies did no
customer outreach or marketing after implementation. It was suggested
that marketing of the passenger information system should be included
within the implementation plans for these systems.

[]{#__RefHeading___Toc138656613 .anchor}4.6 Data Quality

The agencies represented agreed that reliability and data accuracy are
very important. The public needs to feel confident that the information
is accurate and up-to-date to accrue the most benefit from these
systems. The information needs to be kept current and delivered reliably
over time because public use and expectation increases as more
passengers get familiarized with the system. On that regard, the
management of the system data often requires business process
re-engineering and change management to take place within the agency
with the goal of ensuring that system data are maintained and delivered
in a timely and accurate fashion. The use of the information within the
ongoing management and operations performance reporting was a key
consideration for the system.

The participating agencies also stated that good system integration is
important. One important condition to the use and success of passenger
information is an accurate, geo-coded bus stop inventory to each side of
street.

[]{#__RefHeading___Toc138656614 .anchor}4.7 Return on Investment
Analysis

With regards to a ROI analysis of passenger information systems, the
agencies agreed that the process should identify the enabling
technologies first, and then focus on incremental passenger information
(customer-facing) technologies. They also pointed out that passenger
safety and security should be included in the return-on-investment
analysis. They then emphasized the benefit-cost type of approach for the
return-on-investment methodology.

An unanticipated result of the expert panel workshop was the realization
that these agencies are generally not using formal return-on-investment
analyses for their decision making process for these information
systems. None of the participants indicated having performed a formal
ROI analysis for either the real-time info systems or enabling
technologies. In some cases, analytical techniques were used in the
evaluation of alternatives, but not necessarily for the investment
decision. Therefore, the implementing agencies did not have a clear,
objective handle on the value of these investments versus the cost of
implementation.

The largest challenge to developing a formal methodology appears to be
an absence of clear benefits measurements or measures of effectiveness
and significant data quality issues. The agencies and vendors also
emphasized that cost allocation and evaluation of benefits of individual
system components were difficult to address on a segregated level.
Separation of the enabling technologies from the individual systems was
emphasized as a critical issue for the methodology to the project team.

[]{#__RefHeading___Toc138656615 .anchor}4.8 Summary of Surveys

The purpose of the survey was to document implementation, current
deployment and rider use of real-time bus information systems at panel
member agencies. Specifically, the objectives of the survey were to:

-   Identify the real-time information systems deployed by panel member
    agencies and determine the level of deployment (e.g., percent of AVL
    equipped vehicles)

-   Identify all supporting technologies (e.g., AVL/Computer-Aided
    Dispatch (CAD), communications network)

-   Estimate the cost ranges for these systems

-   Determine the number of boardings where passengers used real-time
    information prior to (or during) their trip and the potential
    passenger time savings or other end-user benefits

A description of the survey is included in **Appendix C**. Survey data
were used to help determine the technologies in use and the level of
deployment, and to better understand customer utilization in order to
help measure and aggregate benefits from real-time information. The
following subsections summarize the survey responses received by
technology. The survey was distributed to the 11 participating expert
panel agencies; the total number of respondents was 7:

-   Ride-on (Montgomery County)

-   TriMet (Portland)

-   Arlington County Transit

-   Long Beach Transit

-   Los Angeles County MTA

-   Pace (suburban Chicago)

-   King County Metro

# 4.8.1 Communications Network {#communications-network .FTA-Heading-3}

Most respondents indicated that they have radio communications and
global positioning satellite (GPS) location determination technologies.
One participant responded that they have both cellular and computer wide
area networks along with GPS receivers. The capital cost of
communications networks varied, with a range of approximately
\$2,000-\$3,000 per vehicle. Two agencies reported two separate cost
values, one for replacement and another for upgrade of software and
hardware. Maintenance costs had a higher range of cost values, varying
from \$145 to more than \$650 per vehicle per year. One agency stated
their system was still under warranty and no recurring cost information
was available.

# 4.8.2 Automatic Vehicle Location (AVL) {#automatic-vehicle-location-avl .FTA-Heading-3}

GPS and computer aided dispatch (CAD) systems were the most popular
technologies in AVL systems. Two agencies reported having signpost
positioning devices and, of these, one also indicated having
web-service, telephone and an interactive voice response system as part
of their AVL system.

An estimate of average capital cost per vehicle was difficult to
determine because most of the costs reported were part of a packaged
procurement, which included the tracking/communications systems,
real-time information and other systems. **Table 4-2** summarizes the
cost values reported by four of the agencies.

**Table 4-2**

**Automatic Vehicle Location Systems Costs**

  ----------------- ----------------- ----------------- -------------------
  **Scale of        Capital           Operational       Maintenance
  Deployment**                                          

  240 / 353         **\$6,000,000**   **\$25,000/yr**   \$65,000/yr \*

  \~800 vehicles    **\$6,300,000     **Not reported**  \$50,000/yr for
                    \***                                maintenance
                                                        contract

  30                **\$136,000**     **\$20,000/yr**   \$12,550/yr

  \~1300            \$9,000,000 \*\*  Not reported      Not reported
  ----------------- ----------------- ----------------- -------------------

\* Reported as including the CAD system; \*\* Initial cost plus upgrade

# 4.8.3 Real-Time Information {#real-time-information .FTA-Heading-3}

Four agencies stated having software and server technologies in the area
of real-time information systems. One of the software packages reported
was developed by a local university. The reported capital, operational
and maintenance costs of three of these systems are summarized in
**Table 4-3**. The cost of the real-time system for one of these four
agencies was included in their AVL costs and cannot be separated out.
Therefore, the information is not included in the table.

**Table 4-3**

**Real-time Information Systems Costs**

+---------------+-------------------+------------------+--------------+
| **Scale of    | Capital           | Operational      | Maintenance  |
| Deployment**  |                   |                  |              |
+---------------+-------------------+------------------+--------------+
| 13 wayside    | **                | **Included in    | 0.5          |
| signs         | \~\$10,000/unit** | overall agency   | Full-Time    |
|               |                   | communications   | Employee     |
|               |                   | cost**           | (FTE)        |
+---------------+-------------------+------------------+--------------+
| 4 units       | **\$32,000 plus   | **\$5,000/yr**   | \$4,000/yr   |
|               | \$35,000 for      |                  |              |
|               | software**        |                  |              |
+---------------+-------------------+------------------+--------------+
| Real-time     | \$500,000 for     | \$10,000/yr      | \$10,000/yr  |
| predictions   | Location View     |                  |              |
| at three      | (predicted times  |                  |              |
| transit       | at location)      |                  |              |
| centers and   |                   |                  |              |
| web           | \$232,000 for Map |                  |              |
|               | view (location of |                  |              |
|               | buses)            |                  |              |
+---------------+-------------------+------------------+--------------+

# 4.8.4 Passenger Information {#passenger-information .FTA-Heading-3}

Only three of the seven agencies reported detailed cost information
about passenger information systems. These agencies reported the use of
servers and landline internet as the enabling technologies. The reported
capital, operational and maintenance costs of the other three systems
are summarized in **Table 4-4**.

**Table 4-4**

**Passenger** Information Systems Costs

  ------------------------- ------------------ ---------------- -------------
  **System**                Capital            Operational      Maintenance

  Servers and Landline      **640 programmer                    
  Internet                  hours / year**                      

  Servers                   **\$35,000 / yr**  **\$5,000/yr**   \$4,000/yr

  Real-time predictions at                     \~ \$35,000 / yr 
  three transit centers and                                     
  web.                                                          
  ------------------------- ------------------ ---------------- -------------

# 4.8.5 Phone-Based Information {#phone-based-information .FTA-Heading-3}

Again, only three of the seven agencies recorded responses about
phone-based information (the same three that provided Passenger
Information survey data). All three reported having a customer service
line, with only one of these having a 511 phone system. The third agency
reported had the oldest and largest deployment of these systems,
installed in 1991, with upgrades in 1993, 1996 and 1999, is currently
being replaced. This phone-based information service for this agency
provides scheduled times only, not predicted arrival times. The reported
capital, operational and maintenance costs of the other three systems
are summarized in **Table 4-5**.

**Table 4-5**

**Phone-Based Information** Costs

  -------------- ---------------- ----------------- ------------- -------------
  **Technology   Scale of         Capital           Operational   Maintenance
  Utilized**     Deployment                                       

  Customer       **All buses and  **Included in                   
  Service Line   rail**           web-based                       
                                  development**                   

  Customer       **All revenue    **\$54,000**                    \$4,000/yr
  Service Line   hours**                                          

  Customer       Potential for    \~ \$100,000 in   One Full-time \~ \$5,000/yr
  Service Line,  95%, not         1999              Employee      
  Schedule       currently                                        
  Information,   fully-utilized                                   
  511                                                             
  -------------- ---------------- ----------------- ------------- -------------

# 4.8.6 Wayside Activity {#wayside-activity .FTA-Heading-3}

Four agencies identified some type of wayside or in-vehicle information
technology, such as Dynamic Message Sign (DMS) and Automatic Voice
Annunciation (AVA), implemented on their bus system. The results of the
wayside activity part of the survey are summarized in the **Table 4-6**.

**Table 4-6**

**Wayside Activity Characteristics**

+--------------------+-----------------------------------+-------------+
| **Scale of         | Cost                              | Date of     |
| Deployment**       |                                   | Deployment  |
+====================+===================================+=============+
| 19 DMS             | **\$12,000**                      | 2001-2004   |
+--------------------+-----------------------------------+-------------+
| 13 wayside signs,  | -   **Capital: Approx. \$10,000   | January     |
| with 4 having      |     per unit**                    | 2001        |
| voice annunciation |                                   |             |
|                    | -   **Operational: approaching    |             |
|                    |     zero.**                       |             |
|                    |                                   |             |
|                    | -   **Maintenance: 0.5 FTE**      |             |
+--------------------+-----------------------------------+-------------+
| 4 VMS, 9 Kiosks at | **Not reported**                  | July 2002   |
| points of          |                                   |             |
| interest. AVA on   |                                   |             |
| all fixed routes.  |                                   |             |
+--------------------+-----------------------------------+-------------+
| Flat panel         | -   Cost of computer systems:     | Two         |
| monitors (2) at 3  |     \~\$5,000. Discontinued LED   | locations   |
| transit centers,   |     cost about \$3,000 per sign.  | in late     |
| LED signs (8) on   |                                   | 1990's, one |
| one route.         | -   DSL connection cost           | in 2004.    |
|                    |     \$80/month/location           | LED sign    |
|                    |                                   | demo        |
|                    | -   For LED sign demo, cost of    | available   |
|                    |     \$70/month for cell           | 2004-June   |
|                    |     connection                    | 2005.       |
|                    |                                   |             |
|                    | -   \$1,000/yr for maintenance.   |             |
+--------------------+-----------------------------------+-------------+

[]{#__RefHeading___Toc138656616 .anchor}5.0 RETURN ON INVESTMENT: THEORY
AND APPLICATION

This chapter describes the proposed approach for evaluating the return
on investment (ROI) from future real-time information system
investments. The chapter begins by considering a range of alternate ROI
measures that may be used for such analysis and the traditional
benefit-cost analysis as the preferred approach for this investment
type. Specifically, the benefit-cost analysis provides the best means of
capturing the large potential benefits that accrue to the users of
real-time information systems, benefits not considered by traditional
ROI measures. The chapter then goes on to consider how to apply the
benefit-cost analysis to real-time information system investments. Here,
two options are provided: (1) comparisons of gross investment benefits
to gross investment costs and (2) the use of normalized, cost
effectiveness measures (similar to the cost per new passenger measure
used by Federal Transit Administration's New Starts evaluation process).
Finally, this chapter concludes with the identification of the specific
types of investment benefits that should be included in the evaluation
of real-time information systems, as well as the challenges inherent in
obtaining these cost and benefit data.

[]{#__RefHeading___Toc138656617 .anchor}5.1 ROI Measures and Public
Transit Investments

The objective of return-on-investment measures is to determine how
effective a particular investment has been in generating investment
benefits. Many of these measures have their origin in the private
sector, where for-profit business enterprises continually seek new ways
to reduce unit costs or increase revenues as a means of increasing both
profits and shareholder value. Given these business objectives, many
traditional ROI measures are focused on evaluating investment cost
savings that accrue to the entity (e.g., firm) making the investment,
but place no emphasis on the benefits (or costs) to the investing
entity's customers or to society in general.

Examples of two traditional measures are found in **Table 5-1**,
including the accounting rate of return (ARR) and the payback method.
ARR compares the magnitude of the annual cost savings that result form
making the investment (e.g., cost savings from an improved production
process) with the total cost of that investment. Here, a higher ARR
ratio denotes higher annual investment cost savings as a percent of the
project's investment cost and hence a higher return. Similarly, the
"payback" method relates the initial investment cost to the annual
benefits of that investment [^1]. This provides a crude measure of the
time (in years) required to "pay back" the initial investment cost via
cost savings. A project with a shorter payback period has a higher
return.

Both of these traditional measures suffer from two critical problems.
First, neither method takes into consideration either the "value of
time" (i.e., the fact that a dollar today does not have the same value
as a dollar next year) or the timing of investment costs and benefits
over time. Investment costs (including those for real-time information
systems) are typically greatest in one initial period, whereas
investment benefits (e.g., time savings to riders) may accrue to the
project for many years into the future, a flow of costs and benefits
over time that is not well captured by either of the ARR or payback
methods.

**Table 5-1**

**Evaluation of Return-on-**Investment Standard Methods

+--------------------+-----------------+-------------------------------+
| **Method**         | Approach        | Calculation                   |
+--------------------+-----------------+-------------------------------+
| Accounting Rate of | **Annual cost   | ARR = [Reduction in annual    |
| Return (ARR)       | savings as a    | costs]{.underline}            |
|                    | percent of      |                               |
|                    | initial         | Initial investment cost       |
|                    | investment      |                               |
|                    | cost**          |                               |
+--------------------+-----------------+-------------------------------+
| Payback Method     | **Time taken to | Payback = [Initial investment |
|                    | recoup initial  | cost]{.underline}             |
|                    | investment      |                               |
|                    | cost**          | Annual investment benefits    |
+--------------------+-----------------+-------------------------------+
| Benefit-Cost       | **Benefit-cost  | Determine if:                 |
| Analysis using Net | analysis        |                               |
| Present Value      | determines if   | ∑(Benefits***~t~*** )/(1+*i*) |
| (NPV)\             | discounted      | ***^t^*** \>                  |
| *Preferred method* | investment      | ∑(Costs***~t~***)/(1+*i*)     |
|                    | benefits exceed | ***^t^***                     |
|                    | discounted      |                               |
|                    | costs**         | *Where i is the investor's    |
|                    |                 | cost of capital and t is the  |
|                    |                 | year in which costs and       |
|                    |                 | benefits accrue.*             |
+--------------------+-----------------+-------------------------------+
| Internal Rate of   | Determine       | Find *i* such that:           |
| Return (IRR)       | discount rate   |                               |
|                    | at which        | ∑(Benefits***~t~***)/(1+*i*)  |
|                    | discounted      | ***^t^*** =                   |
|                    | benefits equal  | ∑(Cos                         |
|                    | discounted      | ts***~t~***)/(1+*i*)***^t^*** |
|                    | costs           |                               |
+--------------------+-----------------+-------------------------------+

Second, the ARR and payback measures only measure those investment
benefits that accrue to the entity making the investment (i.e., a profit
oriented business). In other words, these measures do not consider the
value of investment benefits accruing to other potential stakeholders,
including either the firm's customers or to society. This problem
becomes critical when evaluating the investment benefits from real-time
information systems. In particular, the benefits of real-time
information systems accrue primarily to those transit riders using the
information generated by these systems, with few if any benefits
accruing to the transit agency making the investment. Given this
consideration, and the problems cited above, the ARR and payback methods
are considered inappropriate to the problem of evaluating the
effectiveness of investments in real-time information systems.

In contrast to the ARR and payback methods, Table 5-1 provides two
alternative investment return measures better suited to the evaluation
of real-time information system investments. These include net present
value (NPV) based benefit-cost analysis and a related measure, internal
rate of return (IRR). The goal of benefit-cost analysis is to compare
the discounted stream of investment benefits with the discounted stream
of investment costs. The investment is considered to be effective if the
discounted benefits are greater than or equal to the costs. It is
important to note here that benefit-cost analysis offers the following
benefits over the simpler ROI ratios discussed above.

Advantages of Benefit-Cost Analysis:

-   Evaluates the timing of costs and benefits over the full life of the
    project

-   Accounts for the "time value of money"

-   Captures *all* investment costs (capital and operating)

-   Captures the benefits accruing to *all* stakeholders including:

    -   the investing entity (e.g., a transit agency),

    -   other users of the investment (e.g., transit riders) and

    -   society (e.g., from potential reductions in auto use)

-   The ratio of discounted projected benefits to discounted project
    costs (benefit-cost or B/C ratio) provides an accurate measure of
    investment return. Specifically, investments with a B/C ratio \> 1
    represent positive investment returns. The magnitude of the ratio
    denotes the extent to which benefits exceed costs. Alternatively,
    benefit-cost analysis is used to calculate a net investment
    benefits, equal to the project's total discounted benefits less the
    total discounted costs.

Inspection of the calculations in Figure 5-1 above reveals that the
internal rate of return method (IRR) represents a modified application
of the benefit-cost model. Specifically, this method determines the
exact interest rate at which a project's discounted benefits equal its
discounted costs. This rate is then referred to as the IRR. While
offering many of the same benefits of benefit-cost analysis, IRR offers
the additional benefit of determining those interest rate conditions
under which the project has a positive return (i.e., any interest rate
*less* than the IRR). However, by not focusing on the actual cost of
capital, IRR does not measure the actual magnitude of the investment
benefits (i.e., how much bigger are investment benefits as compared to
investment costs?). Also, under some circumstances IRR can generate
*two* interest rate solutions, leaving the analyst to determine which
solution is the correct answer.

Given these issues, it is recommended that discounted benefit-cost
analysis be utilized to evaluate the effectiveness of investments in
real-time information systems.

[]{#__RefHeading___Toc138656618 .anchor}5.2 Application of Benefit-Cost
Analysis to Real-Time Information Systems

Effective application of benefit-cost analysis to the assessment of a
real-time information system investment requires the identification and
collection of all benefit and cost data associated with that specific
investment. A comprehensive discussion of the benefits and costs
associated with real-time information system investments is provided
below. Once collected, these data must then be incorporated into a
benefit-cost model for that investment. A proposed model for the
analysis of real-time information systems is provided in **Equation
5-1** as a benefit-cost ratio, and in **Equation 5-2** as a net benefits
calculation.

$\text{Benefit} - \text{Cost}\ \text{Ratio} = \left\{ \frac{\sum_{t = 1}^{n}\left\{ \left( \left( \text{Users},\ \text{Agency}\  \land \ \text{Social}\ \text{Benefits}_{t} \right) \ast \left( 1 + \text{Rider}\ \text{Growth} \right)^{t} \right)/(1 + i)^{t} \right\}}{\sum_{t = 1}^{n}\left\{ \left( \text{Investment}\ \text{Cost}_{t} + O \land M\ \text{Costs}_{t} \right)/(1 + i)^{t} \right\}} \right\}$
(5-1)

$\text{Net}\ \text{Benefits} = \sum_{t = 1}^{n}\left\{ \left( \left( \text{Users},\ \text{Agency}\  \land \ \text{Social}\ \text{Benefits}_{t} \right) \ast \left( 1 + \text{Rider}\ \text{Growth} \right)^{t} \right)/(1 + i)^{t} \right\} - \sum_{t = 1}^{n}\left\{ \left( \text{Investment}\ \text{Cost}_{t} + O \land M\ \text{Costs}_{t} \right)/(1 + i)^{t} \right\}$
(5-2)

For equations 5-1 and 5-2, *i* is the discount rate, *n* is the life of
the project or investment, and *t* is the project year (from 1 through
*n*).

The numerator of this equation identifies the total benefits accruing to
all investment stakeholders including real-time information system users
(i.e., riders that access the information system), the agency that owns
and operates the system and finally any benefits accruing to society in
general (e.g., if the investment induces increased ridership, society
may benefit from reduced auto travel). Assuming the magnitude of these
benefits are related to the number of riders accessing real-time travel
information, the benefits may then need to be scaled over the life of
the investment (*n)* to capture projected ridership growth.

The denominator of this equation considers the investment's initial
capital cost as well as the ongoing costs to operate and maintain the
real-time information system over the life of the investment. It may
prove necessary to scale these costs to reflect the influences of
increasing operating and maintenance cost with system age as well as any
costs associated with system "modernization" (e.g., web site updates).

[]{#__RefHeading___Toc138656619 .anchor}5.3 Cost Effectiveness Measures

The net-benefits measure shown in equation 5-2 compares a project's
*total* investment benefits with its *total* investment costs. For many
investments, this "total" net-benefits measure can be difficult to
compare across projects and sometimes difficult to interpret within any
given project. For example, consider the benefit-cost analysis of the
two hypothetical project examples in **Table 5-2**. Both projects have
B/C ratios greater than one and positive net benefits. Hence, both
projects have good investment returns. Note, however, that while project
A has the better return per dollar invested, project B provides larger
net benefits (implying that project B is the more expensive). Two
questions arise. First, which of these two projects is the more
desirable? Second, given that the net benefits for a real-time
information system come from a range of sources (potentially including
agency cost reductions, time savings to riders and perhaps local
reductions in auto use), what does it mean to have "\$20 million" in net
benefits?

**Table 5-2**

**Hypothetical** Project Comparisons Using Benefit-Cost Measures

  ------------- ------------ -------------------- ------------------------------
  **Project**   B/C Ratio    Net Benefits (B-C)   Net Benefits per Informed Trip

  **A**         **1.2**      **\$20 million**     \$1.11

  **B**         1.1          \$25 million         \$1.85
  ------------- ------------ -------------------- ------------------------------

One means of addressing these issues is to normalize each project's net
benefits to a common basis. In the case of real-time information system
investments, the logical choice is to evaluate the net benefits of each
investment on a "per informed trip" basis. This calculation is outlined
in **Equation 5-3**.

$\text{Net}\ \text{Benefits}\ \text{Per}\ \text{Informed}\ \text{Trip} = \left\{ \frac{\text{Annual}\ \text{Benefits} - \text{Annual}\ O \land M\ \text{Costs} - \sum_{x}^{}{\text{Annualized}\ \text{Capital}\ \text{Costs}_{x}}}{\text{Informed}\ \text{Trips}\ \text{Per}\ \text{Year}} \right\}$
(5-3)

Here, the numerator compares the annual benefits of the real-time
information system with its annualized capital and operating costs. The
annual benefits are the sum of all benefits to the agency, the
information system users (i.e., information using riders) and any
benefits to society. The annual operating and maintenance (O&M) costs
include all costs to operate and maintain the real-time information
system. Finally, calculation of the annualized capital costs for
component *x* for the investment are provided in **Equation 5-4**, where
*i* is the discount rate. Specifically, this equation shows how to
calculate this value for a specific investment component (e.g.,
electronic information sign). This calculation takes into consideration
the expected useful life of a given component and the agency's cost of
capital to determine the component's expected annualized capital cost.
These annualized capital costs must then be summed across all capital
components to determine the total annualized capital cost for the
investment (see Equation 5-3).

$\text{Annualized}\ \text{Capital}\ \text{Cost}_{\text{Component}\ x}\  = \ \left\{ \frac{i}{1 - (1 + i)^{- (\text{Useful}\ \text{Life})}} \right\} \ast \text{Capital}\ \text{Cost}_{\text{Component}\ x}$
(5-4)

The net annual benefits in the numerator of equation (5-3) are next
divided by the denominator, which is the annual number of trips on which
real-time information is used. This calculation yields a measure of the
net benefits per informed trip. The hypothetical examples on Table 5-2
suggests that project B yields significantly higher benefits per
informed trip, and hence likely represents the better project (on the
assumption that real-time information systems should primarily benefit
agency riders). The example benefit-cost analysis of Portland TriMet's
Transit Tracker information system presented in the next chapter relies
heavily on the approach presented in equation 5-3. FTA also uses a
similar approach with its cost effectiveness measure (cost per new
rider) for New Starts projects.

It is recommended that this approach be considered for future
evaluations of real-time information system investments. In practice, it
may prove difficult to obtain reasonable estimates of annual benefits,
operating and maintenance costs, and/or real-time information system
costs that are representative of the entire life of the project, which
may make use of this approach problematic.

[]{#__RefHeading___Toc138656620 .anchor}5.4 Identification of Investment
Costs and Benefits

Effective application of benefit-cost equations 5-1, 5-2 and 5-3,
require the identification all potential costs and benefits of real-time
bus information systems to all relevant stakeholder groups. The analyst
then needs to collect these data through agency interviews, passenger
surveys and related sources. When identifying and collecting these data,
it is important to consider both qualitative, as well as quantitative
impacts (i.e., costs and benefits) to the transit agency, information
system users, road users and society in general that result from
real-time information system investments. Based on OMB Circular A-4, it
recommended that benefits be reported in three categories:[^2]

> I. Monetized
>
> II\. Quantifiable, but not monetized
>
> III\. Qualitative, but not quantifiable

Benefits should be monetized or at least quantifiable in order to apply
a benefit-cost analysis. However, it is often difficult to monetize
benefits because they are often influenced by numerous contributing
factors, are vaguely defined, or are difficult to measure. For instance,
it is difficult to attribute a ridership increase to a particular
real-time passenger information system implementation without conducting
a controlled experiment[^3]. Short of this, a before/after passenger
survey may suggest an approximate relationship between a change in
customer satisfaction or revealed preference to the frequency of use or
aggregate ridership figures.

[]{#__RefHeading___Toc138656621 .anchor}5.5 System Boundaries

Investment in real-time information systems requires investment both in
the "customer facing" technologies that the riding public can access
(e.g., web sites, phone servers, electronic information signs) and also
in "enabling" technologies that are required for real-time information
systems to function *but which may be implemented independently of the
real-time information system* (e.g., AVL, CAD, Automatic Passenger
Counters). **Figure 5-1** illustrates the independent benefit categories
of the customer facing and enabling technologies. Given that agencies
can and do invest in the enabling technologies without "adding on" an
investment in real-time information systems for riders, the question
arises as to which benefits and costs to include in a benefit-cost
analysis of the real-time information system. In other words, should the
benefit-cost analysis include the costs and benefits of the enabling
technologies or not?

**Figure 5-1**

**Benefits of Enabling Versus Customer Facing Technologies**

There are two cases to consider here. First, if the transit agency
implemented the enabling technologies as a "stand alone" investment and
only implemented the real-time information system "after the fact", then
the real-time information system should be assessed in isolation of all
enabling technology costs and benefits. In contrast, if the transit
agency invested in all technologies simultaneously (both enabling and
customer facing), then the analyst needs to determine whether the
real-time component should or even can be evaluated independently of the
other investments required to support it, but which offer benefits
independent of real-time information to passengers (e.g., AVL). If the
decision is made to include all technologies, then it is only
appropriate to include the benefits of all technologies, not just those
relating to real-time information to passengers. If the purpose of the
analysis is solely to evaluate the return on (the incremental)
investment in real-time information systems, then the benefit-cost
analysis should be limited to costs and benefits relating to the
incremental investment.

[]{#__RefHeading___Toc138656622 .anchor}5.6 Hierarchy of Investment
Benefits

A hierarchical listing or "tree" diagram of the potential benefits of
investment in real-time information systems is provided in **Figure
5-2**. Here, the white boxes represent all of the qualitative,
quantitative, and monetized benefits discussed during the expert panel
workshop, as well as those documented in the panel surveys or in the
literature. Ideally, the list of benefits should be comprehensive,
non-redundant, and mutually-exclusive. In practice, this can be
difficult to accomplish because of interrelationships between benefits
and the challenge of converting non-monetized benefits into current
dollar values for NPV calculations.

The tree diagram captures the linkages between interrelated benefits and
their possible conversion to quantitative measures. If monetized
benefits are not available or not are directly measurable, then a next
best measure may be one of the quantitative benefits presented in the
diagram. There are standard methodologies for transforming quantitative
measures into monetized measures. For example, wait-time or
transfer-time savings as a result of real-time information can be
monetized using a standard "value of time" for different time components
and wage levels[^4]. It is generally accepted that wait time is
perceived to be twice as valuable as time-route or in-vehicle time.

The monetized benefits identified in Figure 5-2 capture all of the
potential benefits of enabling (e.g., communications network, location
technology, computer-aided dispatching) or customer-facing technologies
(e.g., real-time prediction process, pre-trip information, way-side and
in-vehicle information). All are applicable for a benefit-cost analysis
(subject to the caveats of the system boundaries discussion above) with
the exception of increased fare revenue, which would be considered a
transfer between transit riders and the agency/operator. Controlled
experiments or sophisticated survey methods are frequently used to
capture qualitative benefits and convert them to quantitative measures.

**Figure 5-2**

[]{#__RefHeading___Toc138656623 .anchor}5.7 Customer-Facing Technology
Benefits

The qualitative benefits and their relationship to quantifiable benefits
are described in the following paragraphs.

# 5.7.1 Improved Travel/Route Information {#improved-travelroute-information .FTA-Heading-3}

Existing or potential transit riders can use real-time schedule
information to make better decisions about when to initiate a trip,
which services to use, and the expected duration of trips. This can
reduce the overall travel time for users by reducing the wait or
transfer time. Similarly, the availability of vehicle arrival time
reduces traveler uncertainty and the related "wait-time anxiety"
experienced by passengers waiting for the next vehicle to arrive at
their stop. It may also induce new or existing transit riders to select
better travel options/services that have lower travel times than they
would have originally experienced. This can ultimately result in more
frequent or new transit trips. In turn, new transit trips replacing
private vehicle trips can reduce the operations and maintenance costs of
road users by reducing the vehicle miles traveled by private vehicles
including fuel, wear and tear, and insurance rates due to fewer
accidents. It may also reduce congestion levels on roads with fewer
vehicles, which can reduce environmental impact (i.e., air, noise and
water pollution) and save travel time for road users.

# 5.7.2 Improved (actual or perceived) Reliability {#improved-actual-or-perceived-reliability .FTA-Heading-3}

Transit riders may experience or perceive greater service reliability if
enabling technologies are being used to manage and operate the system.
Even if a transit rider does not use "pre-trip" information provided by
customer-facing technologies, studies have shown that passengers are
more satisfied knowing how long the wait will be for the next bus or
when a delay has occurred. Transit riders are more likely to use the
service and potential transit riders are more likely to consider using
the service with improved reliability.

# 5.7.3 Reduced (actual or perceived) Safety/Security Risk {#reduced-actual-or-perceived-safetysecurity-risk .FTA-Heading-3}

Some research suggests that enabling and customer-facing technologies
can at least improve the perceived safety and security of passengers
[^5], shifting ridership patterns if not ultimately increasing ridership
overall. Transit riders may find comfort in knowing that the location of
all vehicles is tracked or in knowing how long they will have to wait
until the next bus arrives.

# 5.7.4 Improved Level Of Service (LOS)/Customer Satisfaction {#improved-level-of-service-loscustomer-satisfaction .FTA-Heading-3}

Customer-facing technologies can increase convenience and quality of
services, and reduce anxiety over delays and other problems. Moreover,
customer complaints about poor or lack of service can be better handled
with documented evidence of actual performance.

[]{#__RefHeading___Toc138656624 .anchor}5.8 Enabling Technology Benefits

# 5.8.1 Improved Schedule/Planning Efficiency {#improved-scheduleplanning-efficiency .FTA-Heading-3}

The monitoring capability of enabling technologies together with the
analysis of the data allows the agency/operator to make better long-term
decisions about service planning. For example, an analysis of operations
and maintenance data provided by enabling technologies can help improve
the accuracy of fleet, labor, equipment and other future requirements.
In essence, better matching the planned supply of services with the
anticipated demand can reduce future vehicle service miles (VSM) and/or
vehicle service hours (VSH). This can ultimately optimize planned
capital investments in vehicles, facilities, and equipment.

# 5.8.2 Improved Operating Performance {#improved-operating-performance .FTA-Heading-3}

Enabling technologies may improve short-term productivity by identifying
and resolving short-term problems in operations and maintenance more
quickly. For example, services that show poor operating performance
(e.g. poor schedule adherence due to recurring congestion) can be
altered to improve productivity and reduce the fleet, labor, equipment
and other material requirements for operations. In essence, enabling
technologies can help utilize resources more efficiently by reducing VSM
and/or VSH while maintaining the level of service.

In addition, enabling technologies enhance the ability to streamline
administrative processes (e.g., billing and payroll) and allow the
flexibility of introducing elements of demand-responsive service (such
as route deviation) into the regular fixed-route services. For example,
paratransit services without AVL/CAD systems required several hours or
even days of advance notice for trip reservations. With modern
technologies, the reservation can be done in much less time or in
real-time.[^6]

# 5.8.3 Improved Incident Response {#improved-incident-response .FTA-Heading-3}

Enabling technologies can improve the response to incidents with
reliable communication channels and location information between a
control center and the vehicles on the street. The control center may be
able to track the location of all vehicles with a certain level of
confidence to determine the impact of an incident or non-recurring
congestion on operations. Dispatchers can use this information to devise
service interventions or emergency operations in real-time.

[]{#__RefHeading___Toc138656625 .anchor}6.0 DEMONSTRATION OF
BENEFIT-COST ANALYSIS PROCESS TRANSIT TRACKER

This section provides a demonstration of how the benefit-cost evaluation
process described in the last section can be applied to an actual
real-time information system investment. The demonstration uses Portland
TriMet's "Transit Tracker" system as the test case.

[]{#__RefHeading___Toc138656626 .anchor}6.1 Introduction

The Transit Tracker system was selected for this demonstration for two
key reasons. First, Transit Tracker has been the subject of multiple
studies. Together, these studies provide a wealth of data regarding
system investment costs (capital and operating), rider use of the
Transit Tracker system and user perceptions of Transit Tracker and how
it has impacted their transit experience (e.g., ease of use, impact on
wait times and wait-time uncertainty). While these studies do not
furnish all of the parameters required for a complete benefit-cost
analysis, they do provide a reliable baseline for formulating that
analysis.

Second, Transit Tracker represents an incremental investment "on top of"
TriMet's existing ITS investments. In other words, TriMet completed
investments in all of those ITS systems required to support Transit
Tracker (i.e., AVL, CAD, communications, etc.) prior to and independent
of its investment in the Transit Tracker system. Hence, investment in
these "supporting" technologies would have occurred even if TriMet had
not made the decision to develop Transit Tracker. This separation of
Transit Tracker from all the preceding (and supporting) ITS investments
provides the case for limiting the benefit-cost analysis to those costs
and benefits directly attributable to the Transit Tracker investment.

At the same time, Transit Tracker has two key limitations that impose
constraints on this benefit-cost demonstration. First, there are
currently no data on key parameters required to complete a comprehensive
benefit cost analysis. These parameters include the number of trips made
using Transit Tracker information, the average time savings realized
from using Transit Tracker (if any) and the value of reductions in
wait-time uncertainty to patrons using Transit Tracker's real-time
information. Second, the Transit Tracker system was designed to be used
by both bus and rail passengers. Because of this, there is no clear and
objective means of fully segmenting either the costs or benefits of the
Transit Tracker system between bus and rail users. For this reason, the
analysis that follows represents an evaluation of the benefits and costs
of Transit Tracker to *all* users (both bus and rail) and not just bus
riders.

It is important to emphasize that the analysis presented here is only a
*demonstration* and does not constitute a full scale benefit-cost
evaluation of the Transit Tracker system. As will become apparent from
the discussion below, there are currently no data available on many of
the key parameters required to conduct a comprehensive benefit-cost
assessment of the Transit Tracker (or any other) real-time information
system. Therefore, the goals of this demonstration are only to (1)
demonstrate *how* a benefit-cost analysis can be completed for a
specific real-time system investment, (2) to highlight the *types of
data* required to conduct a more comprehensive assessment and (3) to
highlight those circumstances required to attain a positive return on
investment in the Transit Tracker system. Ultimately, this analysis
suggests that Transit Tracker likely enjoys appreciable positive net
(social) benefits.

**Comprehensive Analysis Guidelines:** As noted above, this chapter is
intended to provide a demonstration of the application of benefit-cost
principles to a specific real-time information system investment. To
assist in the completion of any future assessments using these
principles, the text below includes shaded boxes (similar to this one)
that outline additional data, steps or analyses that should be included
in a more comprehensive analysis of real-time investment costs and
benefits.

[]{#__RefHeading___Toc138656627 .anchor}6.2 TriMet's Transit Tracker
System

Transit Tracker is a real-time traveler information system deployed by
Portland TriMet beginning in 2001. The Transit Tracker system provides
TriMet riders with a real-time estimate of the expected time until the
next transit vehicle arrives at a specific stop (bus) or station (rail).
Transit Tracker covers all rail stops and each of TriMet's 7,700 bus
stops.

Riders can access Transit Tracker one of three ways:

1.  [At Stops/Stations]{.underline}: Electronic Transit Tracker
    information displays have been deployed at 13 bus stops (4 of which
    also include voice annunciation) and at all TriMet light rail
    stations (deployed January 2001).

2.  [By Phone:]{.underline} TriMet has a dedicated Transit Tracker
    customer service line, 503-238-RIDE (deployed September 2004).

3.  [Via the Web:]{.underline} TriMet has a dedicated Transit Tracker
    web page, <http://www.trimet.org/arrivals/index.htm> (deployed
    September 2002).

Transit Tracker uses global positioning system (GPS) technology to track
the location of vehicles in revenue service. Every TriMet vehicle is
equipped with a transmitter that allows continuous satellite tracking
with an accuracy of approximately 30 feet. This real-time location
information is used to calculate real-time bus and train arrival
information. The information is then routed to electronic displays
(**Figure 6-1**) in equipped bus shelters and rail stations as well as
to the Transit Tracker Online Website (**Figure 6-2**) and related
customer service phone line. Information is provided in the form of
arrival countdowns (i.e., minutes to the next arrival).

![](media/image3.png){width="3.375in" height="2.5in"}

[]{#__RefHeading___Toc138656628 .anchor}6.3 Evaluation Approach

It is hypothesized that the primary benefits of the Transit Tracker
system accrue primarily to users in the form of (1) reductions in wait
time (potentially), (2) reductions in rider's wait-time uncertainty
(i.e., reduced uncertainty regarding the arrival time of the next
transit vehicle) or (3) a combination of these two benefits. TriMet's
surveys and analyses of Transit Tracker use provide a basis for
evaluating these user benefits (e.g., in the form of rider perceptions
regarding wait-time savings, reduced wait-time uncertainty).

It is also possible that better vehicle arrival time information may
also generate additional ridership for TriMet, potentially yielding
additional benefits to society (e.g., from reduced auto use). However,
the existing studies of Transit Tracker use do not

![Sample snapshot of the Transit Tracker website. Transit Tracker allows
users to select a route and direction, and it will display the
approximate arrival time of the next 2 transit
vehicles.](media/image4.png){width="4.5in"
height="2.985433070866142in"}provide a reasonable basis for assessing
any potential increase in ridership resulting from implementation of the
Transit Tracker system. Hence, the potential for increased ridership is
not included as a benefit in this brief demonstration. Similarly, while
TriMet may also enjoy some cost savings benefits from Transit Tracker's
implementation (e.g., a reduction in staff dedicated to customer service
phone lines), TriMet has not conducted studies to measure any such
potential agency cost savings from Transit Tracker implementation.
Therefore such potential agency cost savings benefits are not considered
in this demonstration analysis.

Given these considerations, *this analysis of the Transit Tracker
investment will only focus on the potential benefits from wait-time
savings and reductions in wait-time uncertainty for those travelers
utilizing Transit Tracker information*. In addition, rather than
estimating the aggregate benefits and aggregate costs of transit tracker
use across all users of this information, and then comparing these two
aggregate measures*, this analysis will assess the benefits and costs of
Transit Tracker on a per "informed trip" basis*. This approach, (similar
to the cost effectiveness measure used by FTA for New Starts
investments) offers the benefit of evaluating the "effectiveness" of the
Transit Tracker investment on each trip for which Transit Tracker's
real-time information is used. This approach is also useful in
demonstrating how the net benefits of real-time investment systems like
Transit Tracker are dependent on the number of riders using the system
and the types of benefits enjoyed for each trip for which real-time
information is used. Specifically, net benefits increase as the number
of riders using a real-time information system increases. Net benefits
also increase as wait time decreases and/or as wait-time uncertainty
decreases. A key lesson learned from this analysis is the importance of
marketing real-time information systems to transit patrons to ensure
utilization is as high as possible.

More specifically, the analysis here will consider Transit Tracker's net
benefit per trip using the three individual cases:

> **Case 1 -- Reductions in Wait Time Only:** This case assumes that
> Transit Tracker only generates benefits in the form of reductions in
> wait time for Transit Tracker users. Here, it is hypothesized that
> Transit Tracker users reduce the amount of "padding" they would
> otherwise include in their wait time at transit stops as the next
> vehicle's arrival time is now known with reasonable certainty. In
> other words, Transit Tracker's real-time information allows users to
> delay the time they arrive at their transit stop (internet and phone
> based users) or leave the stop and return later (information display
> users) thus reducing their total wait time and enabling users devote
> the saved time to other uses (e.g., more time at home, in the office,
> running errands, etc).
>
> The application of equation 5-3 for the calculation of the net
> benefits per trip (for trips using Transit Tracker) in this case is
> expressed in **Equation 6-1**.

$\text{Net}\ \text{Benefits}\ \text{Per}\ \text{Trip}_{\text{Case}\ 1}\  = \ $
(6-1)

$$\ \left\{ \frac{\left( \text{Value}\ \text{of}\ \text{Time} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time}\ \text{Savings} \right) - \ \left( \text{Annualized}\ \text{Capital}\ \text{Cost} + \text{Annual}\ O \land M\ \text{Cost} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\}$$

> Note here that the value of time for passengers waiting for a transit
> vehicle has been well documented to be twice the value of time for
> passengers *after* they have boarded the vehicle. Given the US
> Department of Transportation's current value of time for transit
> passengers (in vehicle) of \$11.20 per hour[^7], the value of time for
> transit passengers waiting at stops is therefore estimated to be
> 2\*\$11.20 = \$22.40 per hour. If Transit Tracker users no longer have
> to wait as long at transit stops, they can now apply their "saved"
> time to more productive uses and avoid the discomfort of time spent
> waiting at a transit stop. In effect, this eliminates the \$11.20 in
> extra "cost" associated with the discomfort of waiting for the next
> transit vehicle to arrive, thus reducing the value of time from
> \$22.40 per hour (the wait-time cost) to \$22.40 -\$11.20 = \$11.20
> per hour (the value of time spent in other activities). For this
> reason, the "value of time" used in equation 6-1 is actually *the
> reduction in the wait-time premium* (i.e., \$11.20) and not the full
> value of wait time (i.e., \$22.40).
>
> While 95% of Transit Tracker users agreed the system reduces their
> wait time, there are at present, no solid measures of what the average
> reduction in wait time actually is. Survey responses from users of
> Transit Tracker information displays at equipped bus stops suggests
> that actual reductions in total wait time may be negligible. However,
> this seems unlikely to be the case for those users accessing Transit
> Tracker via either phone or the internet. Given the availability of
> accurate, real-time arrival information, riders accessing Transit
> Tracker via phone or internet have the opportunity of optimizing
> (i.e., delaying) their bus stop arrival time and thus reduce time
> spent waiting a transit stop. Given these considerations, the
> demonstration analysis below will explore the net benefits of Transit
> Tracker use over a range of reductions in average wait time. The
> analysis will similarly consider a range of values for the value of
> time (all based on DOT's published values). Finally, the determination
> of all remaining terms from equation 6-1 (e.g., capital costs,
> operating costs, annual trips using Transit Tracker) are considered
> below.
>
> **Reductions in Wait Time:** As just discussed, the average reduction
> in passenger wait times resulting from Transit Tracker use remains
> uncertain, hence a range of values will be used for this demonstration
> analysis. As one of the primary potential sources of investment
> benefits from real-time information system investment, a more
> comprehensive future analyses of real-time investment benefits will
> need to better research these reductions in passenger wait times.
> Specifically such analyses should conduct separate analyses of the
> reduction in wait time for each of the three primary sources of
> information access, including: via information displays, via phone and
> via the internet. It is hypothesized that time savings will be more
> significant for those accessing real-time information via phone or
> internet as these users have better opportunity to optimize their bus
> strop arrival time. This hypotheses is partially supported by the
> results of Transit Tracker Web use surveys where 94% of users stated
> they can wait longer at home/work before leaving for the bus stop.
>
> **Case 2 -- Reductions in Wait Time Uncertainty Only:** While Case 1
> considered the reduction in total wait time, this case assumes that
> Transit Tracker users only benefit from a reduction in wait-time
> *uncertainty*. As noted above, the value of time for transit riders
> waiting at stops is twice that for riders once they have boarded the
> vehicle. This wait-time premium reflects a variety of wait-time costs
> that are not experienced "in-vehicle" including reduced personal
> comfort (e.g., exposure to the elements), potential safety concerns
> and *uncertainty regarding the arrival time of the next transit
> vehicle*. A key consideration in modeling the value of reducing
> wait-time uncertainty is the absence of any empirical studies that
> estimate what the value of wait-time uncertainty is. In other words,
> how much of the estimated \$11.20 wait-time premium can be attributed
> to wait-time uncertainty: one percent, ninety percent or somewhere
> in-between? This analysis will consider a range of values of the "cost
> of wait-time uncertainty".
>
> The application of equation 5-3 for the calculation of the net
> benefits per trip (for trips using Transit Tracker) for Case 2 is
> expressed in **Equation 6-2**.

$\text{Net}\ \text{Benefit}\ \text{Per}\ \text{Trip}_{\text{Case}\ 2}\  = \ $
(6-2)

$$\ \left\{ \frac{\left( \text{Value}\ \text{of}\ \text{Time} \right) \ast \left( \ \text{Uncertainty}\ \text{Share} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time} \right) - \ \left( \text{Annualized}\ \text{Capital}\ \text{Cost} + \text{Annual}\ O \land M\ \text{Cost} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\}$$

> Here, *Uncertainty Share* is the proportion of the wait-time premium
> associated the uncertainty of transit vehicle arrival times. The
> methodology demonstration will examine this equation with a range of
> wait times.
>
> **Case 3 -- Reductions in Both Wait Time and Wait-Time Uncertainty:**
> Finally, Case 3 considers the case where utilization of Transit
> Tracker information yields reductions in both wait time and wait-time
> uncertainty. The application of equation 5-3 for the calculation of
> the net benefits per trip (for trips using Transit Tracker) for Case 3
> is expressed in **Equation 6-3**. The methodology demonstration will
> examine this equation with a range of wait times.

$\text{Net}\ \text{Benefit}\ \text{Per}\ \text{Trip}_{\text{Case}\ 3} = \ $
(6-3)

$$\ \left\{ \frac{\left( \text{Value}\ \text{of}\ \text{Time} \right) \ast \left\lbrack \left( \ \text{Uncertainty}\ \text{Share}\  \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time} \right) + \left( \text{Wait}\ \text{Time}\ \text{Savings} \right) \right\rbrack - \ \left( \text{Annualized}\ \text{Capital}\ \text{Cost} + \text{Annual}\ O \land M\ \text{Cost} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\}$$

The following sections discuss the data sources for the annualized
capital costs, annual operating costs and number of TriMet trips using
Transit Tracker information.

[]{#__RefHeading___Toc138656629 .anchor}6.4 Transit Tracker Capital and
Operating Costs

Capital and operating costs for the Transit Tracker information system
are provided in **Table 6-1**. These costs have been obtained from prior
published analyses of Transit Tracker investment and operating costs as
well as data obtained directly from TriMet staff (both through phone
interviews and through TriMet's response to the survey for this study).

**Table 6-1**

Transit Tracker Capital and Operation Costs

  ------------------------------------------------------ ----------------
  Capital Costs                                          

  Hardware (primarily field equipment)                   \$ 950,000

  Servers & Software                                     \$125,000

  Total Capital Cost                                     \$1,075,000

  Useful Life (years)                                    

  Hardware (primarily field equipment)                   10

  Servers & Software                                     5

  Cost of Capital (discount rate)                        

  Based on OMB guidelines                                7.0%

  Annualized Capital Cost                                

  Hardware (primarily field equipment)                   \$ 135,259

  Servers & Software                                     \$ 30,486

  Total Capital Cost                                     \$ 165,745

  Annual Operating & Maintenance Costs                   

  Annual Operating Costs                                 \$93,750

  Annual Maintenance Costs                               \$ 558

  Total Annual Operation Cost                            \$94,308

  Total Annualized Costs                                 \$260,053
  ------------------------------------------------------ ----------------

**Collection of Comprehensive Cost Data:** It is important to emphasize
that the cost data collected for this demonstration analysis only
provide a rough approximation of the total capital and operating costs
of the Transit Tracker investment based on published sources and minimal
supplementary data submitted by TriMet in support of this study. A more
comprehensive benefit-cost analysis should include a detailed, primary
data collection effort documenting all project costs. Specifically, a
more detailed and comprehensive cost collection effort should consider:

[Hard Costs (Capital):]{.underline} All "hard" costs including hardware
(e.g., message signs, servers, conduit,), installation costs and parts.

[Soft Costs (Capital):]{.underline} All "soft" costs including project
planning, design and project management. These costs must include the
cost of agency staff time invested in concept development. The cost of
web site programming may be included as either a hard or soft cost.

[Life Expectancy:]{.underline} The life expectancy (in years) of all
hard and soft capital costs. As will be shown below, these life
expectancy values can be used to calculate annualized costs for all
project components.

[Operating and Maintenance Costs:]{.underline} Operating and maintenance
costs must be comprehensive of the cost of all inputs required to
operate and maintain the real-time information system. In addition to
the cost of staff assigned to maintain the equipment, operating costs
must also include the cost of electricity required to power the systems,
as well as parts and equipment utilized by maintenance staff (e.g.,
support vehicles) in conducting their work.

# 6.4.1 Capital Costs {#capital-costs .FTA-Heading-3}

Capital costs for Transit Tracker consist primarily of the cost of
designing, purchasing and installing (including conduit) the Transit
Tracker information displays (dynamic message signs) located at 13 bus
stops and all rail stations. These costs represent the bulk of the
\$950,000 in field equipment cost line item in the Table 6-1[^8]. The
project also included roughly \$125,000 in additional costs for the
purchase of computer servers and web page development[^9].

# 6.4.2 Useful Life, Cost of Capital and Annualized Cost {#useful-life-cost-of-capital-and-annualized-cost .FTA-Heading-3}

Useful life values for capital investments provide a means of
annualizing the cost of project capital investments. The useful life
values for project field equipment, servers and software (i.e., web page
development) are presented above in Table 6-1. These values (in years)
were selected based on the recommendation of TriMet project staff. Next,
the annualization of capital costs requires selection of an appropriate
discount rate or "cost of capital." The discount rate selected for this
analysis was 7.0% as is recommended in the Federal Office of Management
and Budget's guidelines for benefit-cost analyses (OMB Circular A-4,
2003).

Finally, the annualized project capital costs for project hardware,
servers and software development are also presented in Table 6-1 and
total roughly \$166,000 annually. The formula, **Equation 6-4**, used to
calculate the annualized capital cost of each project component is given
by (same as Equation 5-4):

$\text{Annualization}\ \text{Value}\  = \ \left\{ \frac{i}{1 - (1 + i)^{- (\text{Useful}\ \text{Life})}} \right\} \ast \text{Capital}\ \text{Cost}$
(6-4)

Where *i* is the discount rate, Useful Life is the expected useful life
of the project component in years, and Capital Cost is the total cost of
acquiring each project component including design, development,
hardware, installation and project management.

While not required for all approaches to project benefit-cost analyses,
this demonstration analysis used annualized capitalized costs as an
input to the calculation of the total cost of the Transit Tracker
service on a per trip basis.

# 6.4.3 Annual Operating and Maintenance Costs {#annual-operating-and-maintenance-costs .FTA-Heading-3}

Operating and maintenance costs for Transit Tracker consist primarily of
the cost of equipment maintenance (roughly 0.5 FTE annually) plus
equipment power costs. The labor cost for this analysis includes wage,
fringe and overhead. Power consumption was assumed to be 250 watts
priced at 8.5 cents per kWh. While TriMet initially experienced high
communications costs (having contracted communications to an outside
service provider), Transit Tracker now runs on TriMet's own internal
fiber optic communications system, and communications costs are now
negligible.

Based on these assumptions, operating and maintenance costs for Transit
Tracker are estimates to be roughly \$95,000 per year.

# 6.4.4 Total Annual Costs {#total-annual-costs .FTA-Heading-3}

Summing the estimated annualized capital costs with the estimated
operating and maintenance cost yields a total annual cost estimate for
Transit Tracker of roughly \$260,000. Once again, this estimate
represents a best guess based on existing data sources and brief
discussions with project staff solely for the purpose of supporting this
benefit-cost demonstration. A more comprehensive analysis should include
a detailed data collection and documentation effort for all capital,
operating and maintenance costs.

[]{#__RefHeading___Toc138656630 .anchor}6.5 Estimated Number of Uses of
Transit Tracker

Calculation of the net benefits of transit Tracker use on a per trip
basis requires an estimate of the number of trips for which Transit
Tracker information was used. As noted above, TriMet riders can access
Transit Tracker information from three different sources: from Transit
Tracker equipped bus and rail stops, via the internet or via phone.
Following are estimates of the number of trips for which Transit Tracker
information was supplied by each data source.

> **Transit Tracker Information Displays -- Bus Stops**: Transit Tracker
> information displays are currently located at 13 of TriMet's higher
> use bus stops. Based on passenger survey analysis of three of these
> stops, each stop sees between 300 and 1,400 passenger boardings each
> weekday. Annualizing these trips (assuming weekend ridership is 20% of
> daily boardings) yields a *maximum* number of potential Transit
> Tracker users at the 13 equipped bus stops of roughly 2.5 million
> annually. However, it may be assumed that some proportion of these
> riders do not make use of the information provided (e.g., do not leave
> and return later if their bus's arrival time is more then ten minutes
> in the future or, in the case of regular riders, may not read the
> information displays on a regular basis). Similarly, some proportion
> of transit riders using Transit Tracker equipped stops will have
> already obtained bus arrival time information from Transit Tracker via
> either internet or phone *prior* to their arrival at the equipped bus
> stop. It is important therefore to make some further adjustment to bus
> passenger boarding counts when estimating the benefits of Transit
> Tracker use at stops to avoid any double counting (i.e., so as not to
> include web or phone based Transit Tracker users in counts of equipped
> stop users).
>
> **Transit Tracker Information Displays -- Rail Stops**: Transit
> Tracker information displays are also located at all TriMet rail
> stations. Based on National Transit Database (NTD) data, TriMet's
> light rail service had 181.7 million boardings in 2004. As with riders
> at Transit Tracker equipped bus stops, each of these light rail riders
> has the potential to use Transit Tracker information prior to boarding
> the next vehicle. Also similar to bus riders, there is likely a
> significant proportion of riders that either do not make use of
> information supplied by the Transit Tracker information displays or
> have already accessed Transit Tracker prior to arriving at the rail
> station, via either phone or the internet. Hence, 181.7 million
> represents a *ceiling* on annual Transit Tracker use at rail stations.
>
> **Use of Transit Tracker at Bus and Rail Stops:** Passenger surveys
> indicate that 78% of riders at Transit Tracker Equipped bus stops use
> the information frequently or almost always, 11% on an infrequent
> basis and a further 11% rarely or almost never. This analysis did not
> collect similar utilization rate data for rail riders. While this data
> provides a rough means for assessing how many trips for which Transit
> Tracker information is accessed via information display, this
> demonstration will consider the net benefits of the Transit Tracker
> system under a range of trip volumes.
>
> **Transit Tracker Web Site**: The number of transit riders accessing
> Transit Tracker via the internet has grown dramatically since the
> Transit Tracker web site was first introduced in September 2002.
> Specifically, web site use started at roughly 10,000 hits per month
> over the eight months the service was active and reached 66,000 per
> month as of December 2005. This latter usage rate translates to
> roughly 800,000 web hits annually. It is important to consider that
> users may access the Transit Tracker web site multiple times for any
> given trip. Hence, the number of web site "hits" does not necessarily
> represent the number of trips for which Transit Tracker web
> information was used (which is likely less).
>
> **Transit Tracker Web Queries per Trip:** A more comprehensive
> analysis of a real-time information system accessible via the internet
> should attempt to determine the number of times riders query the web
> site for each trip that real-time information is used.
>
> **Transit Tracker Phone Line**: As with web based access, the number
> of transit riders accessing Transit Tracker via phone has grown
> dramatically since this option was first introduced in September 2004.
> Here, the number of calls per month rose from roughly 65,000 calls per
> month over the first year the service was available to an average of
> roughly 225,000 per month over the last four months of 2005. This
> latter usage rate translates to roughly 2.6 million phone calls
> annually. As with web based access, it is important to consider that
> users may access the Transit Tracker phone line multiple times for
> each trip for which real-time information is used. Hence the number of
> phone calls does not necessarily represent the number of trips for
> which Transit Tracker information was used (which is likely less).

Based on this review, a number of conservative assumptions are
considered to calculate a minimum estimated number of trips using
Transit Tracker information, as shown in **Table 6-2**. It is
conservatively estimated that Transit Tracker is likely used for at
least 20 million bus and rail trips each year. Even if use at rail
stations is excluded from the analysis, transit tracker information is
likely used by an estimated 3.4 million trips per year.

**Table 6-2**

Estimated Annual Number of Trips Using Transit Tracker Information

  -------------- ----------------- ----------- -------------------- ----------------
  **Transit      **Maximum Number  **Assumed   **Assumption /       **Minimum
  Tracker        of Trips**        Usage       Justification**      Estimated Number
  Information                      Rate**                           of Trips**
  Source**                                                          

  Transit        2,491,866         50%         Passenger survey     1,245,933
  Tracker                                      result that 78% use  
  Equipped Bus                                 always or frequently 
  Stops                                                             

  Transit        181,760,400       10%         Assumes 1 in 10      18,176,040
  Tracker                                      riders use           
  Equipped Rail                                information display  
  Stops                                                             

  Web Page       792,000           50%         Assumes 2 web hits   396,000
                                               per trip             

  Phone          2,678,694         67%         Assumes 1.5 phone    1,785,796
                                               calls per trip       

  **Total Trips  **187,722,960**                                    **21,603,769**
  using Transit                                                     
  Tracker**                                                         

  **Total Trips  **5,962,560**                                      **3,427,729**
  Excluding                                                         
  Rail**                                                            
  -------------- ----------------- ----------- -------------------- ----------------

[]{#__RefHeading___Toc138656631 .anchor}6.6 Case Evaluations

This demonstration concludes with an analysis of the three cases
outlined in the "Evaluation Approach" section above. Specifically, these
cases examine the potential net benefits of the Transit Tracker system
under the following assumptions regarding system benefits:

> **Case 1:** Transit Tracker only yields benefits in the form of
> reduced wait times
>
> **Case 2:** Transit Tracker only yields benefits in the form of
> reduced wait-time uncertainty
>
> **Case 3:** Transit Tracker yields benefits in the form of both
> reduced wait times and reduced wait-time uncertainty

As discussed above, at present there are no definitive values for
several key parameters required to complete a comprehensive benefit-cost
test. These include the number of trips for which Transit Tracker
information is used, the reduction in wait times for each Transit
tracker "informed trip" and the extent to which the elimination of
wait-time uncertainty reduces the value of time for patrons waiting at
transit stops. Hence, rather than provide a specific benefit-cost return
value for the Transit Tracker system, this analysis will provide
graphical representations of the range of trip volumes, reductions in
wait time and reductions in wait-time uncertainty for which net benefits
of are positive.

**Case 1:** First consider Case 1 (were Transit Tracker yields user
benefits in the form of a reduction in average wait time). The net
benefits for this case were outlined above in equation 6-1. Now consider
the circumstances under which the net benefits for this case are
non-negative. This is provided in **Equation 6-1a**:

$$\ \left\{ \frac{\left( \text{Value}\ \text{of}\ \text{Time} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time}\ \text{Savings} \right) - \ \left( \text{Annualized}\ \text{Capital}\ \text{Cost} + \text{Annual}\ O \land M\ \text{Cost} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\} \geq 0$$

(6-1a)

Substituting in DOT's average value of time and the estimated annualized
capital and operating costs leaves only two remaining variables: average
wait-time savings and annual number of trips using Transit Tracker, as
per **Equation 6-1b**:

$\ \left\{ \frac{\left( \$\text{11}\text{.}\text{20} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time}\ \text{Savings} \right) - \ \left( \$\text{260},\text{053} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\} \geq 0$
(6-1b)

The informed trip volumes and wait-time savings combinations under which
equation 6-1b hold true are presented in **Figure 6-3**. Specifically,
this chart shows the range of informed trip counts and reductions in
average wait time for which the net benefits of investment are greater
than zero. Areas shown in grey have positive net benefits while the area
highlighted in white has negative net benefits. The level of net
benefits increases steadily both as the number of annual informed trips
increases and also as the average reduction in wait times increases.
Note also that the chart presents "break-even" contours for three
different values of time (all from US DOT): the average value of time
(\$11.20 per hour), a low value of time (\$7.90 per hour) and a high
value of time (\$13.40 per hour).

**Figure 6-3**

![](media/image6.wmf){width="6.802083333333333in"
height="4.460416666666666in"}

Figure 6-3, provides the following lessons learned:

-   [Positive Net Benefits Under Reasonable Assumptions:]{.underline}
    The chart demonstrates that net benefits for the Transit Tracker
    investment are positive at relatively small "informed trip" volumes
    and for relatively low reductions in wait times. For example, the
    horizontal white line on the chart shows a very conservative,
    minimum estimate (see Table 6-2) of 3.4 million annual trips for
    which Transit Tracker is used[^10]. At this informed trip volume,
    only a small reduction in total wait time (between 0.5 and 0.75
    minutes per informed trip) is required to attain a positive net
    return. As discussed above, the minimum number of annual trips (bus
    and rail) made using Transit Tracker is estimated at close to 20
    million. For higher informed trip volumes, the total required time
    savings for a positive return drops below 0.25 minutes per informed
    trip.

-   [Minimal Sensitivity to Value of Time:]{.underline} The chart also
    shows little difference in the positions of the three "break-even"
    counters for the low, average and high values of time. Hence, even
    when the value of time is low, Transit Tracker appears to easily
    generate positive net returns at modest informed trip volumes and
    wait-time reduction levels.

-   [Importance of Marketing Availability of Real-Time
    Information:]{.underline} Finally, the chart makes it clear that the
    benefits of Transit Tracker use are directly related to the number
    of trips made using this information. This relationship highlights
    the importance of marketing the availability of passenger real-time
    information to transit riders. The greater the number of users, the
    greater the net benefits. This is especially true in the case of
    information offered via phone or internet, sources that are not as
    apparent to riders as a display sign located at their transit stop
    (these sources also offer the greatest opportunity for a reduction
    in wait time, as these users obtain this information *before* they
    reach their transit stop and hence have better opportunity to
    convert wait time to other, more productive uses).

**Case 2:** For Case 2, Transit Tracker is assumed to only yield user
benefits in the from of a reduction in wait-time uncertainty (as users
are now reasonably certain of the next vehicle's arrival time). The net
benefits for this case were outlined above in equation 6-2. Now consider
the circumstances under which the net benefits for this case are
non-negative. This is provided in **Equation 6-2a**:

$\ \left\{ \frac{\left( \text{Value}\ \text{of}\ \text{Time} \right) \ast \left( \ \text{Uncertainty}\ \text{Share} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time} \right) - \ \left( \text{Annualized}\ \text{Capital}\ \text{Cost} + \text{Annual}\ O \land M\ \text{Cost} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\} \geq 0$
(6-2a)

Substituting in DOT's average value of time and the estimated annualized
capital and operating costs again leaves only three remaining variables:
uncertainty share, average wait time and annual number of trips using
Transit Tracker, as per **Equation 6-2b**:

$\ \left\{ \frac{\left( \$\text{11}\text{.}\text{20} \right) \ast \left( \ \text{Uncertainty}\ \text{Share} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time} \right) - \ \left( \$\text{260},\text{053} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\} \geq 0$
(6-2b)

The informed trip volumes and average wait time combinations under which
equation 6-2b hold true are presented in **Figure 6-4**[^11].
Specifically, areas shown in grey have positive net benefits (depending
on the uncertainty share) while the area highlighted in white has
negative net benefits. The level of net benefits increases steadily both
as the annual number of informed trips increases and also as the total
wait time increases. Finally, note that the chart shows varying
"uncertainty shares". As discussed above, this is the proportion of the
wait-time premium that is attributable to wait-time uncertainty. Once
again, the wait-time premium is a measure of rider discomfort due to
exposure to the elements, potential safety concerns as well as wait-time
uncertainty experienced while waiting at a transit stop. Given that the
proportion of the wait-time premium attributable to wait-time
uncertainty is unknown, this analysis considers a range of values from a
minimum of 5% to a maximum of 50%.

**Figure 6-4**

![](media/image7.wmf){width="6.935416666666667in"
height="4.460416666666666in"}

Figure 6-4, provides the following lessons learned:

-   [Positive Net Benefits Under Reasonable Assumptions:]{.underline}
    The chart demonstrates that net benefits for the Transit Tracker
    investment are again positive at relatively small informed trip
    volumes and for typical wait times. For example, the horizontal
    white line on the chart once again shows the very conservative
    estimate of 3.4 million annual trips for which Transit Tracker is
    used (see Table 6-2). Similarly, the vertical lines show both the
    average wait time at Transit Tracker equipped bus stops (8.5
    minutes) as well as one-half the average headway on TriMet's higher
    frequency bus routes (roughly 7.5 minutes). Hence, the coordinates
    of TriMet's actual average wait time and Transit Tracker informed
    trips most likely lie *above* the horizontal line and *near* the two
    vertical lines. Note that all of these potential points only require
    a 5% reduction in the wait-time premium (or even less) to attain a
    positive net benefit.

-   [Sensitivity to Uncertainty Share:]{.underline} As the uncertainty
    share increases from 5% to 15% or more, the average wait time
    required for a positive net benefit drops from roughly eight minutes
    to only three minutes or less at low informed trip volumes and to
    one minute or less for high informed trip volumes.

**Case 3:** Finally, Case 3 represents a combination of Case 1 and Case
2. Here, it is assumed that Transit Tracker use yields reductions in
both average wait time and wait-time uncertainty. The net benefits for
this case were outlined above in Equation 6-3. Now consider the
circumstances under which the net benefits for Case 3 are non-negative.
This is provided in **Equation 6-3a**:

$\ \left\{ \frac{\left( \text{Value}\ \text{of}\ \text{Time} \right) \ast \left\lbrack \left( \ \text{Uncertainty}\ \text{Share}\  \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time} \right) + \left( \text{Wait}\ \text{Time}\ \text{Savings} \right) \right\rbrack - \ \left( \text{Annualized}\ \text{Capital}\ \text{Cost} + \text{Annual}\ O \land M\ \text{Cost} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\} \geq 0$

(6-3a)

Substituting in DOT's average value of time, the estimated annualized
capital and operating costs and an assumed uncertainty share of 25% now
leaves *three* remaining variables: average wait time, average wait-time
savings and annual number of trips using Transit Tracker. This yields
**Equation 6-3b**:

$\ \left\{ \frac{\left( \$\text{11}\text{.}\text{20} \right) \ast \left\lbrack \left( \text{25}\text{\%} \right) \ast \left( \text{Avg}\text{.}\ \text{Wait}\ \text{Time} \right) + \left( \text{Wait}\ \text{Time}\ \text{Savings} \right) \right\rbrack - \ \left( \$\text{260},\text{053} \right)}{\text{Annual}\ \text{Number}\ \text{of}\ \text{Trips}\ \text{Using}\ \text{Transit}\ \text{Tracker}\ \text{Information}} \right\} \geq 0$
(6-3b)

The conditions under which **Equation 6-3b** hold true are presented in
**Figure 6-5**[^12]. In order to represent the three unknown variables
in this equation, the points at which the net benefits of Transit
Tracker investment are zero is represented in this chart as a three
dimensional surface. Hence, any point *above* this surface represents a
positive net benefit for Transit Tracker. Specifically, this chart shows
the range of informed trip counts, average wait times and reductions in
wait time for which the net benefits of investment are greater than
zero. Once again, this chart suggests positive net returns under fairly
conservative assumptions. For example, under the assumption of an
average wait time of six minutes (less than half the average headway for
high-frequency bus routes) and a two-minute reduction in average wait
time, Case 3 predicts that Transit Tracker only needs to be used on
roughly 400,000 trips annually to generate a positive net benefit.
**Table 6-3** provides a range of informed trip volumes required to
attain positive net benefits for given average wait times and Transit
Tracker induced reductions in wait times.

**Figure 6-5**

![](media/image8.wmf){width="6.678472222222222in"
height="4.409027777777778in"}

**Table 6-3**

**Case 3: Minimum Number of Annual Transit Tracker**

Informed Trips Required to Attain Positive Net Benefits

  -------------------------- ------------- --------- --------- --------- ---------
  **Average Wait Time        **Average                                   
  (minutes)**                Reduction in                                
                             Wait Time                                   
                             (minutes)**                                 

  ***Determines wait-time    **1.0**       **2.0**   **3.0**   **4.0**   **5.0**
  uncertainty***                                                         

  **2.0**                    928,762       557,257   398,041   309,587   253,299

  **4.0**                    696,572       557,257   398,041   309,587   253,299

  **6.0**                    557,257       398,041   309,587   253,299   214,330

  **8.0**                    464,381       348,286   278,629   232,191   199,020
  -------------------------- ------------- --------- --------- --------- ---------

^\*^ Assumes \$11.20 value of time and 25% reduction in wait-time
premium (i.e., 25% uncertainty share)

[]{#__RefHeading___Toc138656632 .anchor}6.6 Conclusion

This brief demonstration has outlined the types of information required
to conduct a benefit-cost analysis of a real-time information system,
using TriMet's Transit Tracker system as a test case. In addition to
highlighting the information needs associated with this type of
analysis, this demonstration has also outlined the circumstances
required to attain a positive net benefit for the Transit Tracker
system. Using fairly conservative assumptions regarding, informed trip
volumes, reductions in wait time and reduction in the cost of wait-time
uncertainty, it was shown that Transit Tracker most likely achieves
positive net (social) benefits.

[]{#__RefHeading___Toc138656633 .anchor}6.7 Future Applications and
Enhancements

The results from this development of the return on investment approach
for real-time bus arrival passenger information systems may be applied
in a potential, future field test and return-on-investment study. As
existing systems become more widely implemented and accepted by the
transit rider, the benefits of these systems can be more clearly
demonstrated. Options include those transit systems with existing
passenger information systems such as:

-   TriMet

-   Los Angeles County MTA

-   King County Metro

-   San Francisco Muni

-   Pace (suburban Chicago)

-   Denver RTD

-   Fairfax CUE

-   Cape Cod Regional Transit Authority

-   AC Transit (Oakland, CA)

-   Portland Streetcar

This process can also be applied with other systems investments within
the overall Intelligent Transportation Systems (ITS) realm. The FTA will
determine if the subsequent field test and return-on-investment study
are needed.

[]{#__RefHeading___Toc138656634 .anchor}BIBLIOGRAPHY

# APPLICABLE DOCUMENTS

The following documents may be used as resources.

-   *Guidance for Developing and Deploying Real-time Traveler
    Information for Transit*, developed by Battelle for the Federal
    Transit Administration and U.S. DOT ITS Joint Program Office, April
    30, 2003, U.S. DOT \# FTA-OH-26-7017-2003.1

-   *TCRP Synthesis 48: Real-time Bus Arrival Information Systems*,
    Transit Cooperative Research Program, Transportation Research Board,
    2003

-   *Oregon Regional Intelligent Transportation Systems (ITS)
    Integration Program Draft Phase III Report: Transit Tracker
    Information Displays*, developed by Science Applications
    International Corporation (SAIC) for the U.S. DOT ITS Joint Program
    Office, October 7, 2003

-   *Oregon Regional Intelligent Transportation Systems (ITS)
    Integration Program Final Phase II Report*, developed by Science
    Applications International Corporation (SAIC) for the U.S. DOT ITS
    Joint Program Office, July 12, 2002

-   *Transit Tracker Evaluation Final Report*, Tri-County Metropolitan
    Transportation District of Oregon (TriMet) Marketing Information
    Department, June 2002

[]{#__RefHeading___Toc138656635 .anchor}APPENDIX A: Agenda -- August 9,
2005

**[FTA Real-Time Bus Arrival Information Systems ROI
Study]{.underline}**

**Expert Panel Meeting**

Montgomery County Public Safety Communications Center (PSCC), "Situation
Room"

1300 Quince Orchard Blvd., Gaithersburg, Maryland 20878

9:00 AM Reception

9:15 Welcome Alfie Steele, Montgomery County

Opening Remarks and Overview of Study Objectives Brian Cronin, FTA

Introductions

Motivation for Study and Role of Expert Panel Donald Schneck, Booz Allen

George Darido, Booz Allen

Discussion of Technologies and System Boundaries David Jackson, Booz
Allen

Proposed Benefit-cost Analysis Approach Rick Laver, Booz Allen

\- Methods for evaluating return-on-investment

\- Identification of costs and benefits

12:00 PM Lunch

1:00 On-Site Tour/Demonstrations

Continued Discussions to Quantify Costs and Benefits

> \- Unit cost information
>
> \- Documented studies on system impacts
>
> \- Other data available

Discussion of Barriers to Successful Implementation Rick Laver, Booz
Allen

4:00 Summary and Wrap-up Donald Schneck, Booz Allen

4:30 Adjourn

[]{#__RefHeading___Toc138656636 .anchor}APPENDIX B: List of Participants
to August 9, 2005 Expert Panel Workshop

  ---- ----------- ----------------- ------------------ ---------------- -------------------------------------
       **Name**    **Title**         **Organization**   **Phone**        **Email**

  1    Ms. Lurae   Program Manager   APTA               202-496-4844     lstuart@apta.com
       Stuart                                                            

  2    Ms. Kelley  Operations        Arlington County   703-228-7547     kmackinnon@arlingtonva.us
       MacKinnon   Manager           Transit                             

  3    Mr. Don      Senior Associate Booz Allen         267-330-7992      schneck_donald@bah.com
       Schneck                                                           

  4    Mr. Rick    Associate         Booz Allen          703-902-4676     Laver_richard@bah.com
       Laver                                                             

  5    Mr. Dave     Associate        Booz Allen          319-361-0007     Jackson_David@bah.com
       Jackson                                                           

  6    Mr. George   Sr. Consultant   Booz Allen         703-377-4059      Darido_georges@bah.com
       Darido                                                            

  7    Mr. Gerry   Manager,          Chicago RTA        312-913-3251     tumbalig@rtachicago.org
       Tumbali     Engineering &                                         
                   Technology                                            

  8    Mr. Robert  Managing Director Connexionz         +64-3-339-4536   robert.burke@connexionz.co.nz
       Burke                                                             

  9    Mr. Alex    Transportation    Fairfax County     703-385-7889     averzosa@fairfaxva.gov
       Verzosa     Director                                              

  10   Ms.         Project COTR      FTA                 202-366-1077     Charlene.wilder@fta.dot.gov
       Charlene                                                          
       Wilder                                                            

  11   Mr. Eric    Community Planner FTA                                  Eric.pihl@fta.dot.gov
       Pihl                                                              

  12   Mr. Paul    Economist         FTA                 202-366-1675     Paul.marx@fta.dot.gov
       Marx                                                              

  13   Mr. Brian    ITS Team Leader  FTA                 202-366-8841     Brian.cronin@fta.dot.gov
       Cronin                                                            

  14   Ms. Aletha  Transp. Program   FTA                202-366-4148     Aletha.goodine@fta.dot.gov
       Goodine     Spec.                                                 

  15   Mr.          General Engineer FTA                 202-366-0244     Sebastien.renaud@fta.dot.gov
       Sebastien                                                         
       Renaud                                                            

  16   Mr. Tom     Project/Program   King County Metro  206-684-1513     tom.friedman@metrokc.gov
       Friedman    Manager           Transit                             

  17   Ms. Carri   Project Manager   Long Beach Transit 562-599-8527     csabel@lbtransit.com
       Sabel                                                             

  18   Mr. Joe     Asst. Director of LACMTA             213-922-3877     vicentej@mta.net
       Vicente     Information                                           
                   Systems                                               

  19   Mr. Steve   Lead Transport    Mitretek Systems    202-488-1504     Steven.mortensen@mitretek.org
       Mortensen   Planner                                               

  20   Mr. Alfie   Ride On Transit   Montgomery County  240-777-5845     alfie.steele@montgomerycountymd.gov
       Steele      Central Dispatch                                      

  21   Mr. Joe     National Sales    Next Bus           415-218-7926     jmonaco@nextbus.com
       Monaco      Director                                              

  22   Mr. Marc     Deputy GM        Orbital TMS        443-259-7163     gordon.marc@orbital.com
       Gordon                                                            

  23   Mr. Mike    Asst Exec         Pace Suburban Bus  847-228-2305     michael.bolton@pacebus.com
       Bolton      Director                                              

  24   Mr. Eric    Director of       Potomac and        703-580-6117     emarx@omniride.com
       Marx        Planning and      Rappahannock TC                     
                   Operations                                            

  25   Ms. Patty   Project Manager   San Francisco MUNI 415-701-4303     patty.devlieg@sfmta.com
       DeVlieg                                                           

  26   Mr. Bill     Manager Business Siemens            319-743-1011     bill.hiller@siemens.com
       Hiller      Development                                           

  27   Mr. Jack    Chief of Bus      WMATA              202-962-1319     jrequa@wmata.com
       Requa       Operations                                            

  28   Mr. Peter   IT Project        WMATA              202-962-2614     jmeenehan@wmata.com
       Meenehan    Manager                                               
  ---- ----------- ----------------- ------------------ ---------------- -------------------------------------

[]{#__RefHeading___Toc138656637 .anchor}APPENDIX C: Survey Description

**1. Technologies**

The first block of the survey consisted of indicating the agency's
current deployment and level of investment in Real-Time Bus Information
Systems. Agencies were asked to provide the following inputs for each of
the types of technologies indicated:

+--------------------+----------+----------+-------------+-----------+
| **Technology**     | **Utili  | **Cost** | **Scale of  | **Date    |
|                    | zation** |          | Imple       | Impl      |
|                    |          |          | mentation** | emented** |
+--------------------+----------+----------+-------------+-----------+
|                    | *Type of | *        | *Level of   | *When did |
|                    | te       | Capital, | deployment  | the       |
|                    | chnology | O        | (number of  | t         |
|                    | in use*  | perating | buses,      | echnology |
|                    |          | and      | sites,      | become    |
|                    |          | Mai      | etc.)*      | oper      |
|                    |          | ntenance |             | ational?* |
|                    |          | (total   |             |           |
|                    |          | or per   |             |           |
|                    |          | unit)*   |             |           |
+--------------------+----------+----------+-------------+-----------+
| -   Communications |          |          |             |           |
|     Network        |          |          |             |           |
|     Investments    |          |          |             |           |
|     (integration   |          |          |             |           |
|     of system      |          |          |             |           |
|     components)    |          |          |             |           |
+--------------------+----------+----------+-------------+-----------+
| -   Automatic      |          |          |             |           |
|     Vehicle        |          |          |             |           |
|     Location       |          |          |             |           |
|     (AVL/CAD and   |          |          |             |           |
|     AVL only)      |          |          |             |           |
+--------------------+----------+----------+-------------+-----------+
| -   Real-Time      |          |          |             |           |
|     Prediction     |          |          |             |           |
|     Process        |          |          |             |           |
|     (software,     |          |          |             |           |
|     servers)       |          |          |             |           |
+--------------------+----------+----------+-------------+-----------+
| -   Passenger      |          |          |             |           |
|     Information    |          |          |             |           |
|     Web-site       |          |          |             |           |
+--------------------+----------+----------+-------------+-----------+
| -   Phone-Based    |          |          |             |           |
|     Information    |          |          |             |           |
|     Systems        |          |          |             |           |
+--------------------+----------+----------+-------------+-----------+
| -   Wayside        |          |          |             |           |
|     Activity       |          |          |             |           |
|     Center /\      |          |          |             |           |
|     In-Vehicle     |          |          |             |           |
|     Information    |          |          |             |           |
+--------------------+----------+----------+-------------+-----------+

**2. Customer Use of Real-Time Information Systems**

The second block of the survey was a series of questions regarding rider
use of real-time information systems. Participants were asked to answer
the following questions:

1.  Has your agency determined how many riders utilize your real-time
    information system options? If yes, how did your agency measure the
    rate of utilization and what was the estimated rate of use (e.g.,
    web site hits)?

2.  Is use of your real-time information confined to a limited set of
    knowledgeable users (e.g., younger users with greater technology
    awareness)? Do you know how frequently riders make use of such
    information (daily, weekly, monthly, less)?

3.  If you have more than one real-time information source option, which
    source(s) do riders use most of (e.g., phone based, internet, kiosk,
    other)?

4.  Has your agency conducted marketing campaigns to generate awareness
    of the real-time information systems?

5.  Have riders provided feedback on the usefulness and quality of
    real-time information systems?

6.  Has your agency evaluated the benefits to riders of using real-time
    information (e.g., time savings, awareness of service disruptions)?

7.  Has your agency collected data or completed studies on rider use of
    real-time information that could be of use to this study? Can you
    provide copies of these materials?

    1.  **Customer Use of Real-Time Information Systems**

The responses of survey questions are tabulated below.

1)  *Has your agency determined how many riders utilize your real-time
    information system options? If yes, how did your agency measure the
    rate of utilization and what was the estimated rate of use (e.g.,
    web site hits)?*

+-------+--------------------------------------------------------------+
| **S   | **Response**                                                 |
| urvey |                                                              |
| Num   |                                                              |
| ber** |                                                              |
+-------+--------------------------------------------------------------+
| 1     | No                                                           |
+-------+--------------------------------------------------------------+
| 2     | \~65,000 calls/month. \~12,500 web site hits/month.          |
+-------+--------------------------------------------------------------+
| 3     | Based on our normal website visitors sessions, the average   |
|       | is running around 4000 per month, which translates into      |
|       | about 6% of ridership                                        |
+-------+--------------------------------------------------------------+
| 4     | Not yet. Real-time information not implemented on our web    |
|       | site: planned for end of October 2005. Intend to incorporate |
|       | questions about our VMS into our annual customer             |
|       | satisfaction survey.                                         |
+-------+--------------------------------------------------------------+
| 5     | No real-time information system available for all our        |
|       | services: on a limited basis. Several bus stops on our Rapid |
|       | Bus Systems display next bus arrival time: not operating at  |
|       | this time due to equipment upgrade.                          |
+-------+--------------------------------------------------------------+
| 6     | Webwatch is the system provided to passengers. In January    |
|       | 2005, 12000 visits to the site, it is being used about 7000  |
|       | times per month on average. IP addresses are tracked to know |
|       | unique users: on average there are 3361 unique users per     |
|       | month.                                                       |
+-------+--------------------------------------------------------------+
| 7     | Survey to evaluate LED demo project yielded positive         |
|       | feedback on reliability of messages displayed and making     |
|       | transfers easier.                                            |
|       |                                                              |
|       | Survey conducted at two transit centers where bus status     |
|       | video monitors were installed: 3 of 4 respondents were aware |
|       | of system (22% always use it, 28% sometimes use it, 26%      |
|       | rarely use it, 25% never seen it)                            |
+-------+--------------------------------------------------------------+

2)  *Is use of your real-time information confined to a limited set of
    knowledgeable users (e.g., younger users with greater technology
    awareness). Do you know how frequently riders make use of such
    information (daily, weekly, monthly, less)*

+-------+--------------------------------------------------------------+
| **S   | **Response**                                                 |
| urvey |                                                              |
| Num   |                                                              |
| ber** |                                                              |
+-------+--------------------------------------------------------------+
| 1     | Don\'t know                                                  |
+-------+--------------------------------------------------------------+
| 2     | Web site: 76% use it frequently or almost always; 37%        |
|       | female, 63% male; 81% \<45 years, none 65+, 42% 25-34; 32%   |
|       | ride bus every day. Wayside: 75% use it frequently; 54%      |
|       | female, 46% male; 79% \<45 years, 1% 65+, 38% 17-24; 68% 30  |
|       | bus trips in previous month.                                 |
+-------+--------------------------------------------------------------+
| 3     | Real-time will be available to all riders.                   |
+-------+--------------------------------------------------------------+
| 4     | No. Real-time information currently only provided on 4 VMS   |
|       | on a single corridor and 9 kiosks at our Downtown Transit    |
|       | Mall                                                         |
+-------+--------------------------------------------------------------+
| 5     | No real-time information system available for all our        |
|       | services: on a limited basis. Several bus stops on our Rapid |
|       | Bus Systems display next bus arrival time: not operating at  |
|       | this time due to equipment upgrade.                          |
+-------+--------------------------------------------------------------+
| 6     | Do not have profile for the typical user other than the      |
|       | anecdotal number. Not yet surveyed to find out how often     |
|       | people make use of the info.                                 |
+-------+--------------------------------------------------------------+
| 7     | LED signs installed as a demo project (2 bus stops).         |
|       |                                                              |
|       | Survey of bus status video monitors: Regular users           |
|       | (responded to always using system) are slightly younger,     |
|       | more educated, and technologically savvy. Majority of survey |
|       | respondents were long-term bus users with high awareness of  |
|       | schedules.                                                   |
+-------+--------------------------------------------------------------+

3)  *If you have more than one real-time information source option,
    which source(s) do riders use most of (e.g., phone based, internet,
    kiosk, other)?*

  ---------- --------------------------------------------------------------
  **Survey   **Response**
  Number**   

  1          Don\'t know

  2          Probably web.

  3          Undetermined at this point

  4          N/A

  5          Not applicable at this time except for a few bus stops on the
             Rapid Bus Lines where next bus arrival time is displayed.
             There is a project to provide real-time information by phone,
             internet and kiosk.

  6          Most customers still use the phone. Kiosk information in the
             beginning stages, data unknown at this moment.

  7          N/A
  ---------- --------------------------------------------------------------

4)  *Has your agency conducted marketing campaigns to generate awareness
    of the real-time information systems?*

  ---------- --------------------------------------------------------------
  **Survey   **Response**
  Number**   

  1          No

  2          Yes; mostly for phone and web systems.

  3          An extensive plan is in place to launch system wide: forums,
             info on websites, management meetings at metro stops, press
             releases, etc.

  4          Initial marketing campaign done when larger system was
             deployed, which included info on our web site, brochures
             available on all buses, bus kings and tails and a television
             commercial.

  5          No

  6          We had a campaign that made people aware of the new system. We
             are planning a bigger campaign when we have the map option
             available on line.

  7          No marketing of LED demo project
  ---------- --------------------------------------------------------------

5)  *Have riders provided feedback on the usefulness and quality of
    real-time information systems?*

+-------+--------------------------------------------------------------+
| **S   | **Response**                                                 |
| urvey |                                                              |
| Num   |                                                              |
| ber** |                                                              |
+-------+--------------------------------------------------------------+
| 1     | Very little                                                  |
+-------+--------------------------------------------------------------+
| 2     | Web site: 96% agreed easy to use; 95% agreed saves time. 86% |
|       | frequently or almost always accurate. Wayside: 60% placed    |
|       | highest value of all amenities; 89% frequently or almost     |
|       | always accurate.                                             |
+-------+--------------------------------------------------------------+
| 3     | No live data available yet but based on the frequency of     |
|       | requests from passengers, it is believed it will be very     |
|       | successful. Currently, alerts via Website, PDA, email.       |
+-------+--------------------------------------------------------------+
| 4     | N/A                                                          |
+-------+--------------------------------------------------------------+
| 5     | No, no real-time traveler information system except in a few |
|       | bus stops on the Rapid Bus.                                  |
+-------+--------------------------------------------------------------+
| 6     | Unsolicited comments have been quite favorable.              |
+-------+--------------------------------------------------------------+
| 7     | Survey after LED demo project reveal positive responses on   |
|       | LED signs. Respondents were satisfied with quality of        |
|       | message (information displayed, length of message, etc.)     |
|       |                                                              |
|       | Survey of bus status video monitors: 80% of regular and      |
|       | occasional users of the system felt monitors were accurate   |
|       | all or most of the time. 75% of regular users indicated      |
|       | information about actual and scheduled departure times and   |
|       | description of route numbers was very useful (most           |
|       | occasional users found these "somewhat useful"). Most        |
|       | respondents thought quality and location of screens were     |
|       | acceptable ("good" or "ok")                                  |
+-------+--------------------------------------------------------------+

6)  *Has your agency evaluated the benefits to riders of using real-time
    information (e.g., time savings, awareness of service disruptions)?*

  ---------- --------------------------------------------------------------
  **Survey   **Response**
  Number**   

  1          No

  2          Web site: 95% agreed saves time, 94% decided to wait longer
             before leaving home or work for bus stop after checking web
             site. 90% used it to minimize their wait time. Wayside: 42%
             now know how long they have to wait; 19% know exactly when the
             bus will arrive. 60% cited reduced anxiety.

  3          See \# 5, Data used internally to test new routes & tweak
             current routes

  4          No. This is something that is being pushed from the bottom up.
             Currently reviewing an ITS Strategic Plan that recommends a
             Steering Committee take on this task.

  5          Not yet. Will do after real-time traveler information system
             is implemented

  6          Questions will be included on customer satisfaction survey
             that will be conducted next spring.

  7          Survey of bus status video monitors asked attitudinal and
             behavioral questions of users: analyses suggest users view
             system as real benefit (more than just cosmetic), through
             peace of mind or flexibility. However, it does not
             significantly increase satisfaction with decision to use the
             bus.
  ---------- --------------------------------------------------------------

7)  *Has your agency collected data or completed studies on rider use of
    real-time information that could be of use to this study? Can you
    provide copies of these materials?*

-   "Customer Satisfaction with Real-time Arrival Information in
    Portland, Oregon," submitted to 83rd Annual TRB Meeting, January
    2004, Science Applications International Corporation.

-   "Transit Tracker Evaluation, June 2002, Final Report," TriMet
    Marketing Information Department.

-   "Oregon Regional Intelligent Transportation Systems (ITS)
    Integration Program, Final Phase III Report: Transit Tracker
    Information Displays," November 2003, Science Applications
    International Corporation.

-   "Real-Time Bus Information Sign: LED Demonstration Project report."
    King County.

-   "TransitWatch: Bus Status Video Monitors in Seattle." Customer
    Satisfaction Evaluation. King County.

# CONTACT INFORMATION {#contact-information .unnumbered}

Task Order Manager: Ms. Charlene Wilder

Office of Research, Demonstration and Innovation

Federal Transit Administration

400 7^th^ Street, S.W. Room 9402

Washington, DC 20590

[^1]: Note that if the benefits included in the payback method are
    limited to only the annual cost savings resulting from the
    investment, then the payback method is merely the inverse of the ARR
    method (i.e., Payback = 1/ARR)

[^2]: Office of Management and Budget, Circular A-4 issued September 17,
    2003, page 45.

[^3]: Ridership increases can result from a wide variety of factors
    included economic and population growth, changes in passenger fares,
    seasonal fluctuations and other factors. Given these sources of
    variation, it is difficult to attribute changes in ridership to any
    specific sources (e.g., introduction of a real-time information
    system). Hence, to effectively identify any ridership increases
    resulting specifically from a real-time information system
    investment would require a controlled experiment where the
    information system is only deployed on a portion of an agency's bus
    network, thus providing a basis to distinguish increases in
    ridership from the new information system versus other factors.

[^4]: For further information on value of time, the reader is referred
    to Chapter 3 of TCRP Report 78 "Estimating the Benefits and Costs of
    Public Transit Projects: A Guidebook for Practitioners," 2002.

[^5]: USDOT Report by SAIC, "Oregon Regional Intelligent Transportation
    Systems Integration Program: Final Phase III Report: Transit Tracker
    Information Displays," November 2003.

[^6]: Zhong-Ren Peng, et al. "Evaluation of the Benefits of Automated
    Vehicle Location Systems for Small and Medium Sized Transit
    Agencies." paper presented at the Transportation Research Board
    Annual Meeting, 1999.

[^7]: Determination of the value of time for use in Federal
    transportation analyses is provided the Office of Secretary of
    Transportation (OST). See:
    http://ostpxweb.dot.gov/policy/Data/VOTrevision1_2-11-03.pdf

[^8]: Note: This includes roughly \$750,000 for the initial investment
    (see TCRP #48) and an additional \$200,000 to equip TriMet's Red
    Line.

[^9]: Web page development only required 640 programmer hours. In
    addition to the cost of web servers, the \$125,000 for servers and
    software includes and estimate of the programmer's wage, fringe and
    overhead costs. Finally, the server and programming costs were
    further inflated by roughly forty percent to include the cost of
    project conceptual design and development by TriMet staff. As noted
    in the shaded box above, a more comprehensive analysis should
    document each of these costs in full based on TriMet records and
    additional interviews with project staff.

[^10]: This estimate of 3.4 million annual "Transit Tracker informed"
    trips assumes that: (1) Transit Tracker is only used by half of bus
    riders at equipped stops, (2) that web users access the Transit
    Tracker web site twice on average per trip and (3) that phone users
    access Transit Tracker 1.5 time per trip on average. This estimate
    also excludes use at rail stations. Per trip here refers to the
    number of trips for which Transit Tracker information was used, not
    the total number of transit trips.

[^11]: Note: This chart assumes an average value of time of \$11.20 per
    hour.

[^12]: Note: This chart assumes an average value of time of \$11.20 per
    hour.