Enhanced Genetic Algorithm for Signal-Timing Optimization of Oversaturated Intersections

Author:

“Brian” Park Byungkyu1,Messer Carroll J.2,Urbanik Thomas3

Affiliation:

1. National Institute of Statistical Sciences and North Carolina State University, Research Triangle Park, NC 27709-4006

2. Texas Transportation Institute, CE/TTI Building Suite 304C, College Station, TX 77843-3135

3. Texas Transportation Institute, 109 Gibb Gilchrist Building, College Station, TX 77843-3135

Abstract

Enhancements were provided to a previously developed genetic algorithm (GA) for traffic signal optimization for oversaturated traffic conditions. A broader range of optimization strategies was provided to include modified delay minimization with a penalty function and throughput maximization. These were added to the initial delay minimization strategy and were further extended to cover all operating conditions. The enhanced program was evaluated at different intersection spacings. The optimization strategies were evaluated and compared with their counterpart from TRANSYT-7F, version 8.1. A microscopic stochastic simulation program, CORSIM, was used as the unbiased evaluator. Hypothesis testing indicated that the GA-based program with average delay minimization produced a superior signal-timing plan compared with those produced by other GA strategies and the TRANSYT-7F program in terms of queue time. It was also found from the experiments that TRANSYT-7F tended to select longer cycle lengths than the GA program to reduce random plus oversaturation delay.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

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