基于黄金分割双种群遗传算法的区域交通信号控制

Regional Traffic Signals Control with Golden Ratio Dual Population Genetic Algorithm

针对非均匀交通流的城市区域信号配时优化问题,以区域总通行能力和总延误为优化目标,构建基于目标相对占优策略的城市区域交通信号优化模型;在采用遗传算法求解优化模型时,由于遗传算法易早熟收敛会导致寻优效果不佳,因此引入黄金分割法对双种群遗传算法进行改进,两个种群同时且独立地进行寻优操作,并进行个体交换,避免算法陷入局部最优的陷阱,利用4个常用的测试函数验证算法有效性,实验结果表明改进的算法能够快速搜索到全局最优解;最后对所提的模型和算法进行有效性评价,结果表明,所建模型符合实际交通控制目标并且计算简单,验证了模型的有效性;所改进的算法在城市区域路网中能够有效地获得良好的信号配时方案。

Aiming at the problem of urban regional signal timing optimization with non-uniform traffic flow,the regional total capacity and total delay are taken as the optimization goals,and the urban regional traffic signal optimization model based on the target relative dominance strategy is constructed.When the genetic algorithm is used to solve the optimization model,because the genetic algorithm tends to converge prematurely,the optimization effect is not good.Therefore,the golden ratio method is introduced to improve the dual population genetic algorithm.The dual population simultaneously and independently perform optimization operations and exchange individuals to prevent the algorithm from falling into the trap of local optimization.Use 4 commonly used test functions to verify the algorithm validity,and the experimental results shows that the improved algorithm can quickly search for the global optimal solution.Finally,the effectiveness of the proposed model and algorithm is evaluated,and the results show that the built model meets the actual traffic control goals and the calculation is simple,which verifies the effectiveness of the model;the improved algorithm can effectively obtain a good signal timing scheme in the urban area road network.