城市交通拥挤问题的探讨

本文探讨了城市交通拥挤问题的解决方法．根据道路的拥挤状况引入畅通度的概念，量化了道路的拥挤程度．在道路的物理距离的基础上加入畅通因素把它转化为一种新的距离，这样使原有寻找最短路径的算法能继续适用．同时本文详细介绍了公路网络中信息的存储方法：Coordinate Storage（COO），Compressed Sparse Row（CSR），Compressed Sparse Column（CSC），Block Sparse Row，以及最短路径的搜索算法：Dijkstra算法和Bellman—ford算法，同时给出了Dijkstra算法步骤和它的最新改进算法．

A Discussion of the Traffic Jam Problem in Cities

This paper discusses the method of solving the problem of traffic jam in cities.According to the status of jam we introduce a concept called expediency,making the status of expediency measurable,menawhile,we add the expediency factor into the physical distance and get a new kind of distance so that the algorithm searching for shortest path can still be suitable.Besides this paper talks about the storage methods:Coordinate Storage(COO),Compressed Sparse Row(CSR),Compressed Sparse Column(CSC),Block Sparse Row,and the shortest path algorithm:Dijkstra algorithm and Bellman-ford algorithm,then we give the steps of dijkstra algorithm and its latest speed-up algorithm.