面向城市交通网络的一种新型动态路径寻优方法

 针对静态路径寻优方法中没有考虑到交通流随时间变化的问题,本文提出一种基于交通流量预测的路径寻优方法.首先,从实际交通路网本身的特点和人类对路网的认识出发,构建以"道路"为基本元素的新型路网模型;其次,采用基于单变量时间序列的预测方法对路网上各路段未来一段时间内的道路交通流量进行预测,并根据预测结果估计出行者在未来时段各路段上的交通代价;再次,通过估计的交通代价把车辆从起点到该路段时间内的道路交通变化状况融入改进A^*算法的路径搜索过程,从而建立一种高效的动态改进A^*路径搜索算法;最后,实例表明预测交通流量与实际交通流量具有很好的拟合度,路径搜索结果能够对出行者起到诱导作用,提高出行者行驶效率.

A Novel Dynamic Path Optimization Method for Urban Traffic Networks

Aiming at the problem that traffic flow varying with the departure time has not been taken into account in static path optimization method,a path optimization method based on traffic flow prediction is proposed.First of all,a novel road-based model,based on the characteristics of traffic network and the human’s understanding to the road traffic network,is constructed.Then,a prediction method based on single time series is adopted to obtain the future information of traffic flow of road sections,and transportation cost of travelers for each section is estimated by the forecast result.Next,the change of road traffic situation during the traveling from the origin to the destination is integrated into path search process of improved A^* algorithm by the estimated transportation cost,thus a high efficient dynamic improved A^* algorithm for path optimization is obtained.Finally,the path-search examples show that the predicted traffic flow and measured traffic flow can march well,thus the path searching result can guide travelers to improve their driving efficiency.