交通流诱导与控制协同优化模型的遗传算法求解

Application of genetic algorithm in coordination optimization model between traffic flow guidance and traffic control

以路段和交叉口的加权拥挤程度最小为目标,建立诱导和控制的协同优化交通流分配模型,并提出基于遗传算法的求解。采用动态滚动式计算模型算法得出的均衡流量调整为诱导信息的发布提供定量依据,能够将诱导和控制协同起来均衡路网流量,避开拥挤。小路网试验结果表明:该模型算法实时、有效,便于实施。

A traffic flow assignment model for the coordination optimization between the traffic flow guidance and the traffic control was built with minimizing the integrated weighted congestion rate of both the road section and the intersection as the optimization target, and the genetic algorithm was applied to solve the model. The adjustment to equilibrate the road network traffic flow from the coordination between the guidance and control obtained from the real-time roiling computing the model is a nice quantitative support to provide the guidance information for the vehicle drivers to aooid traffic congestion. The test on a small road network proved the algorithm of the model is characterized by good realtimeness high effectiveness and easy implementation.