公交优先下交叉口配时优化的双层模型与遗传算法

Bi-level Optimization Model of Intersection Timing About Bus Priority Condition Based on Genetic Algorithm

在综合分析各类城市交叉口特性基础上,对传统的信号配时方法进行了理论改进,针对设有公交专用道的交叉口建立了公交优先交叉口配时的双层模型,并利用遗传算法对该模型进行了定量求解.VISSIM仿真实验结果表明:与传统配时方法相比,该模型不仅降低了乘客在交叉口的人均延误和车辆在车道上的平均运行延误,而且在保障交叉口交通顺畅的前提下实现了公交优先,同时未过多损害社会车辆的通行效益.

Based on the integrated analysis of properties of the various urban intersections, the authors theoretically improve the traditional signal timing method, build the double-layer model under bus priority condition targeting at the intersections equipped with bus lanes, and carry on the quota calculation to this model using the genetic algorithm. The experiment results of the VISSIM simulation indicate better performances of the proposed model. Compared with the traditional timing method, the model not only decreases the average delay for both per passenger at the intersection and bus vehicles＇ running in the lanes, but also realizes the bus priority with causing no impairment to other vehicles＇ efficiency as well as guaranteeing the traffic at the intersection running smoothly.