【摘要】 传统的交通控制方法采用基于时间延迟的红绿灯调度方法和车辆限行,路径规划等简单的措施,无法针对实时的车辆信息进行不断调整和反馈达到最优效果。提出了一种基于随机邻阶点选择进化的交通控制优化方法,采用随机临界点模型将所有的分析对象车辆纳入分析范围,然后依据随机邻阶点选择进化的方法,对每个车辆的最佳全局路线进行选择进化,不断迭代,得出最优化的全局方法。采用实际的某地区交通进行测试实验,结果显示,采用基于随机邻阶点选择进化的方法,交通通行率提高46.8%,优化率提高34%,具有很好的指导意义。更多还原

【Abstract】 An optimized traffic control method with random neighbor point selection and evolution was proposed, all the vehicles were included in the scope of analysis objects, and then the random neighbor point evolutionary approach was choose to select the best overall course of evolution for each vehicle constantly iteration, draw global optimization method, a regional transportation actual was used to do test experiments, the results show that with random neighbor point choose evolutionbased approach, the traffic pass rate increased 46.8% and the improvement rate was increased with 34%, it has good application for guidance.更多还原