Research on Analysis Method of Traffic Congestion Mechanism Based on Improved Cell Transmission Model

To analyze the spreading regularity of the initial traffic congestion, the improved cell transmission model (CTM) is proposed to describe the evolution mechanism of traffic congestion in regional road grid. Ordinary cells and oriented cells are applied to render the crowd roads and their adjacent roads. Therefore the traffic flow could be simulated by these cells. Resorting to the proposed model, the duration of the initial traffic congestion could be predicted and the subsequent secondary congestion could be located. Accordingly, the spatial diffusion of traffic congestion could be estimated. At last, taking a road network region of Hangzhou city as an example, the simulation experiment is implemented to verify the proposed method by PARAMICS software. The result shows that the method could predict the duration of the initial congestion and estimate its spatial diffusion accurately. 1. Introduction The urban traffic congestion has been becoming a more and more serious issue, especially in China. Traffic congestion is a typical traffic condition with a dynamic course by time. The congestion generating mechanisms analysis considering both time and space scale helps to illustrate the dynamic changing characteristic of the traffic flow that eventually leads to the congestion. Many scholars had studied the urban traffic congestion by cell transmission model (CTM) at the 1990s [1–3]. Some scholars, such as Szeto, Jia Bin et al., had researched CTM model to have a good performance in simulating the typical dynamic characteristics of traffic flow, such as the formation of shock waves, traffic congestion, and the dynamic evolution rule of node combined by Multiroad [4, 5]. Certainly, other scholars, such as Chen Qian, ZHOU Xi-peng, and YANG Zhao-shen, applied CTM model to the models of traffic flow spread on network such as traffic bottleneck recognition and modeling for traffic events duration time and traffic recovery time [6–10]. In previous studies, the spatial diffusion estimating and duration predicting of traffic congestion are separately supposed as both independent issues on congestion. However, both issues usually affect and restrain one another. Actually they have remarkable relationship in time and space scale. Therefore, the analysis method based on our proposed improved CTM model will give a new solution to track traffic congestion considering both time and space scale. And the research in this paper promises to prevent and relieve traffic congestion and improve the utilization efficiency of the road resources. This paper is organized as follows.