关键词: 多目标优化, 人工鱼群算法, 云遗传算法, 信号交叉口配时方案优化

Abstract: Due to the impact of signal timing schemes on the traffic efficiency of intersections, in order to improve the operation status of intersections, this paper constructs an intersection signal timing optimization model with the optimization objectives of vehicle delay, number of stops and delay imbalance, and uses an improved artificial fish swarm algorithm to solve the problem. It introduces attenuation functions in the improved algorithm to obtain variable step size and variable field of view. By combining the crossover and mutation operations genetic algorithm in artificial fish movement strategy, a cloud model is used to generate new crossover and mutation probabilities to optimize crossover and mutation operations. Finally, a certain intersection in Chongqing is selected as a case study, and VISSIM software is used for experimental simulation to compare and analyze the impact of the current timing scheme and the optimized scheme on the operational efficiency of the intersection. The results show that the application of this method can reduce vehicle delay, parking times and queue length, effectively improving the traffic efficiency of road intersections.