关键词: 智能交通, 交通信号, 相关性分析, 配时模型, 遗传算法, 黄金分割

Abstract:

Aiming at the problems of the local optimum of the genetic algorithm in solving traffic signal timing models, this paper presents an optimized traffic signal controller with a golden ratiobased genetic algorithm (TSCGRGA) for urban signalized intersections. This controller employs numerical simulation to analyze the correlation between the traditional performance indicators of traffic signal benefit and their correlation degree with timing parameters, select time delays, stop rate and throughput to establish relative evaluation indices of traffic signals, and a multiobjective timing model of traffic signals is developed by weighted coefficient method. Then, an adaptive golden ratiobased genetic algorithm is presented to solve the optimized models, which uses real number encoding, and introduces golden ratio calculator to enhance the local optimal capability of genetic algorithm. Experiments are conducted on a typical urban isolated intersection and the performance of the developed model and algorithm is validated by comparison with those of fixedtime, actuated, and simple realcoded genetic algorithmbased controllers for different traffic conditions. Extensive numerical circulation and VISSIM simulation results have demonstrated the potential of the developed algorithm in the quality of solutions and time efficiency, and indicated that the signal strategies derived from TSCGRGA have better performance.

Key words: intelligent transportation, traffic signal, correlation analysis, timing model, genetic algorithm, golden ratio