Neural-network-based cycle length design for real-time traffic control

Author:

Kim Jin-Tae123,Lee Jeongyoon123,Chang Myungsoon123

Affiliation:

1. Division of Traffic Management and Planning, Seoul Metropolitan Police Agency, No. 201-11 Jongro-gu Naeja-dong, Seoul, South Korea.

2. The Korean Road and Transportation Association, KooSang Building 4F, Daechi1-dong, Kangnam-gu, Seoul, 135-838, South Korea.

3. Department of Transportation and System Engineering, Hanyang University, No. 1271 Sa 1 dong, Ansan, Kyunggi-do, 425-170, South Korea.

Abstract

Adaptive traffic control systems (ATCS) are designed to calculate traffic signal timings in real time to accommodate current traffic demand changes. A conventional off-line computer-based design procedure that uses iterative evaluations to select alternatives may not be appropriate for ATCS due to its unstable searching time. Search-free analytical procedures that directly find solutions have been noted for ATCS for this reason. This paper demonstrates (i) the shortcomings of an analytical cycle-length design model, specifically COSMOS, in its ability to generate satisfactory solutions at various saturation levels and (ii) an artificial neural network (ANN) based model that can overcome these shortcomings. The ANN-based model consistently yielded cycle lengths that ensure a proper operational target volume to capacity (v/c) ratio, whereas the use of the analytical model resulted in unstable target v/c ratios that might promote congestion.

Publisher

Canadian Science Publishing

Subject

General Environmental Science,Civil and Structural Engineering

Reference17 articles.

1. Evaluation of New Jersey Route 18 OPAC/MIST Traffic-Control System

2. SCOOT and Incidents: Performance Evaluation in Simulated Environment

3. Evaluation of CORSIM Car-Following Model by Using Global Positioning System Field Data

4. Fu, L. 1994. Neural network in computer intelligence. McGraw-Hill, Inc., New York.

5. Hale, D.K. 2004. Traffic network study tool, TRANSYT –7F, United States version. McTrans Center, University of Florida, Gainesville, Fla.

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