Transportation Operations Coordinating Committee System for Managing Incidents and Traffic: Evaluation of the Incident Detection System

Abstract

The Transportation Operations Coordinating Committee’s System for Managing Incidents and Traffic (TRANSMIT) is an operational test that uses vehicles equipped with tags of the E-ZPass electronic toll collection system as traffic probes for traffic surveillance and incident detection. The TRANSMIT incident detection algorithm is based on statistical comparison of real-time estimates of travel times with continuously updated historical travel times for the same time period of the day and type of day (weekday, Saturday, Sunday, or holiday). The probability of detecting an incident and the false-alarm rates produced by TRANSMIT during a 4-month evaluation period (January to April 1996) may be considered excellent for the data collected on the New York State Thruway and satisfactory for the data collected on the Garden State Parkway. The mean time to detection of an incident was not estimated at this stage of the evaluation. The TRANSMIT communication system exhibited excellent performance in terms of the transmission rates systemwide, which were found to be near 100 percent. Only the radio link at Tappan Zee Bridge exhibited a lower transmission rate. A limited probe vehicle test was conducted to determine the detection rate at individual roadside terminals. The lower detection rates observed were site specific rather than systemwide. The performance of the TRANSMIT incident detection algorithm performed very favorably compared with the performances of the best incident detection algorithms reported in the literature.

Get full access to this article

View all access options for this article.

References

Marshall

K. R.

, and Batz

. The TRANSCOM Transmit Project: An Alternative Approach for Traffic Surveillance and Incident Detection. TRANSCOM, Jersey City, N.J., 1995.

Mouskos

K. C.

, and Niver

. TRANSMIT System Evaluation Test Plan. New Jersey Institute of Technology, Institute for Transportation, Newark, N.J., 1996.

Suggested Evaluation Test Plan (ETP) Format. Booz Allen & Hamilton, Inc., McLean, Va., 1995.

Mouskos

K. C.

, Niver

, Pignataro

L. J.

, Lee

, Antoniou

, and Papadopoulos

. Evaluation of the TRANSMIT System. Final Report. Institute for Transportation, New Jersey Institute of Technology, June 1998.

Marshall

K. R.

TRANSMIT Incident Detection Algorithm. PB Farradyne, Inc., 1995.

Batz

TRANSMIT-TRANSCOM’s System for Managing Incidents and Traffic. TRANSCOM, Jersey City, N.J., 1995.

Special Report 209: Highway Capacity Manual. TRB, National Research Council, Washington, D.C., 1994.

Collins

J. F.

, Hopkins

C. M.

, and Martin

J. A.

. Automatic Incident Detection—TRRL Algorithms HIOCC and PATREG. Supplementary Report 526. Transport Research Laboratory, 1979.

Levin

, and Krause

G. M.

. Incident Detection: A Bayesian Approach. In Transportation Research Record 682, TRB, National Research Council, Washington, D.C., 1978, pp. 52–58.

10.

Payne

, and Tignor

S. C.

. Freeway Incident Detection Algorithms Based on Decision Trees with States. In Transportation Research Record 682, TRB, National Research Council, Washington, D.C., 1978, pp. 30–37.

11.

Persaud

, Hall

, and Hall

. Congestion Identification Aspects of the McMaster Incident Detection Algorithm. In Transportation Research Record 1287, TRB, National Research Council, Washington, D.C., 1990, pp. 167–175.

12.

Dudek

, Nuckles

, and Messer

. Incident Detection on Urban Freeways. In Transportation Research Record 495, TRB, National Research Council, Washington, D.C., 1974, pp. 12–24.

13.

Cook

A. R.

, and Cleveland

D. E.

. Detection of Freeway Capacity-Reducing Incidents by Traffic-Stream Measurements. In Transportation Research Record 495, TRB, National Research Council, Washington, D.C., 1974, pp. 1–11.

14.

Ahmed

S. A.

, and Cook

A. R.

. Discrete Dynamic Models for Freeway Incident Detection System. Transportation Planning & Technology, Vol. 7, 1982.

15.

Richie

, and Cheu

. Simulation of Freeway Incident Detection Using Artificial Neural Networks. Presented at 75th Annual Meeting of the Transportation Research Board, Washington, D.C., 1996.

16.

Stephanedes

, and Liu

. Artificial Neural Networks for Freeway Incident Detection. In Transportation Research Record 1494, TRB, National Research Council, Washington, D.C., 1995, pp. 91–97.

17.

Chang

, and Wang

. Improved Freeway Incident Detection Using Fuzzy Set Theory. In Transportation Research Record 1453, TRB, National Research Council, Washington, D.C., 1994, pp. 75–82.

18.

Stephanedes

, Chassiakos

, and Michalopoulos

. Comparative Performance Evaluation of Incident Detection Algorithms. In Transportation Research Record 1360, TRB, National Research Council, Washington, D.C., 1992, pp. 50–57.

19.

Subramaniam

Literature Review of Incident Detection Algorithms to Initiate Diversion Strategies. Working paper. University Center for Transportation Research, Virginia Polytechnic Institute and State University, Blacksburg, 1991.