基于SPEA2的城市快速路速度引导多目标优化

Multi-objective Optimization of Urban Expressway Speed Guidance Based on SPEA2

基于速度引导控制作用下的城市快速路交通流扩展模型,建立了车辆总耗费时间与速度引导值变化幅度的多目标优化模型。采用强度Pareto进化算法(SPEA2)对比分析3种速度引导值确定方案,同时基于集合理论从Pareto前沿中选择出最优解并确定最佳方案。在此方案下,应用Matlab进行了速度引导控制仿真分析,结果表明,速度引导控制对于缓解交通拥挤具有良好效果,可为主动交通管理在城市快速路中应用提供理论支持。

Based on the extended model of dynamic traffic flow on urban expressway under speed guidance control, a multi-objective optimization model was established based on the total travel time of vehicles and the value of speed guidance changes. Three scenarios of speed guidance value were compared with improved Strength Pareto Evolutionary Algorithm （SPEA2）. Then the best solution was selected from Pareto front and the optimal scenario was determined based on set theory. Simulation analysis of speed guidance control was carried out in Matlab simulation platform under the optimal solution. The results show that speed guidance control has a good effect for alleviating traffic congestion and improving traffic safety which can provide a theoretical support for active traffic management of urban expressway.