Traffic Congestion Analysis of Shanghai Road Network Based on Floating Car Data

With the rapid growth of urban traffic, the contradiction between traffic demand and supply has become increasingly conspicuous, and traffic congestion has become a normal state. How to identify the frequent congested road sections, estimate their influence to the entire road network; and how to improve the connectivity and accessibility of the whole road network through local traffic reformation, have become important issues to transportation planners and managers. In this paper, we take Shanghai as an example. We analyze the spatio-temporal characteristics of urban traffic congestion, and identify the frequent congested sections in the network, using floating car data. Furthermore, we revealed the correlation of spatial distribution and the spatial concentration characteristic of congestion, by global and local spatial autocorrelation analysis.