A Simulation Of The Traffic Behavior At Propagation Of Urban Coincidental Traffic Jams Based On Cellular Automata Model

In recent years, with the increasing urban population and vehicle, urban traffic congestion has greatly affected the quality of urban residents’life, and caused great waste to the urban road resources and the city economic. According to the causes of congestion, urban road traffic congestion can be divided to occasional congestion and regularity congestion. You can predict regularity congestion based on survey data and experience to take measures to control. The occasional congestion has occurred in the random time and space, but also has a great derivative. Its impact is often greater influence compared to regularity congestion.Currently, many scholars are working on occasional congestion problems, and get certain achievement. Due to the sudden and accidental of urban coincidental traffic jams, it is difficult to forecast the time and place of it take place, which affects the city road traffic network seriously. In this paper, the behavioral of the driver was consider to the rule of driver change of lanes, and a new rules of the changes of lanes consider of the combination of driver behavioral and coincidental traffic was put forward, then a improved cellular automaton model was put forward this paper, it was proposed to describe the characteristics of coincidental traffic jams. By the proposed model, the velocity of traffic flow and the length of vehicle lines up by coincidental traffic jams was simulated, and the results of simulation was proposed also.In this paper, the first chapter describes the background and significance of urban road congestion propagation, which focused on analysis and discussion of the current research, and some research results in practical application and methods of traffic flow simulation. The second chapter described the characteristics of the road traffic state, mainly described the classification of urban road traffic and basic principles of road traffic parameter selection, different comparisons road of traffic flow characteristics, and described methods of measurement of road traffic conditions. The third chapter introduces the impact source and classification of urban traffic congestion formation, simply analyzed the use of the impact source of urban road incidental congestion and propagation based on the wave theory. The fourth chapter discussed the classic cellular automaton traffic flow model, and then based on these models to establish an improved cellular automaton model for road traffic incidental congestion modeling, optimized the road rules and the vehicle following behavior on impact factors for the vehicle driver behavior, and the city main roads, secondary roads, freeway congestion and different regions were modeled. The fifth chapter made a simulation analysis on the traffic parameters and queue length of the traffic incidental congestion under different road conditions. And comparatively analyzed the impact on the different parameters caused by different densities, the number of lanes, probability of lane changing, and to verify the feasibility of the model also.