Research and analysis on causality and spatial-temporal evolution of urban traffic congestions-a case study on Shenzhen of China

Traffic congestion is a widely existed social economy problem in metropolitans, which brings huge cost to many cities and urban areas. The direct reasons for traffic congestion are the rapid increasing number of automobiles, and comparable insufficient of transportation facilities, however different cities and regions may have their particular characteristics. This paper investigated the inherent principles of spatial-temporal evolution of traffic congestion based on Shenzhen floating car data (FCD) and geo-simulation platform. GIS technologies were used to match the congestion state along the road network, so that the evolution pattern of congestions could be analyzed. Moreover, a correlation algorithm was proposed to measure the similarity of congestion patterns between different links quantitatively, which assists to analyze and disclosure the principles of congestion evolution, and thus to provide guidelines for congestion mitigation. The algorithm can be implementated to integrate the surveilance of traffic congestion with urban planning and management, so as to improve the efficiency of entire transportation system.