城市交通拥挤问题的探讨(英文)

A Discussion of the Traffic Jam Problem in Cities

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 SparseColumn(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.

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.