Study On Traffic Flow Model Based On Cellular Automata Theory

With the development of national economy, the people's demand of transportation becomes increasingly expanding. The contradiction between the growth of traffic volume and the road condition is becoming prominent, which has greatly restricted the development of the social economy. The aim of traffic flow research is to build traffic flow model which can describe the general properties of the real traffic. Thus, researching on traffic flow theory is not only profound scientifically significant, but also valuable for engineering application.Based on cellular automata theory, the dissertation has a research on the model building, simulation and application of the traffic cellular automata (TCA) models. The main results achieved in this dissertation can be summed up as follows.a) We classify the traffic cellular automata models to single-cell model and multi-cell model according to the cell number each vehicle occupied and one dimensional model, two dimensional model according to the dimension the model revolved. Based on JAVA , we simulate each TCA model's time-space diagram or traffic fundamental diagram. And then, based the simulations and real data, we give some analysis and evaluations of each traffic cellular automata model.b) An improved NS-TCA model is presented and we incorporate its slowdown probability to the macroscopic first-order LWR model. Then, we rebuild the first-order LWR model's traffic fundamental diagrams. Based on simulations and real data, the method is approved to be effective and can reflect the real traffic flow characteristic. Furthermore, based on the relationship of the one dimension stochastic traffic cellular automata model and the first-order LWR model which the dissertation discovered, we interpret the dynamics feature of the traffic flow.c) We incorporating the origin-destination (OD) effect of vehicles to the famous two dimensional city traffic cellular automata model—BML model and present two extended models. We first define the origin and destination coordinates origin-destination distance and the measure means of OD distance. Then, we use three different distributions: exponential, uniform and power-law and build two extended BML model. Based on simulation, it is approved that using our models, we can adjust the origin-destination distance probability distributions to enhance the road capacity of the city and to minimize the arrival time of vehicles.d) Based on the efficient computation of traffic cellular automaton, combining a departure time choice model with a dynamic route choice model, and incorporating a dynamic network loading model, we build a frame of dynamic traffic assignment system.e) Supported by GIS, using the traffic cellular automata models mentioned above, we present a kind of data structure to implement the dynamic traffic assignment system. In this data structure, we built the node structure, link structure and origin-destination structure which contain multi-modes and can be easily extended. We transform these data structures to the attribute data and implement the dynamic traffic assignment system in GIS using the Taian city's urban OD data. According to the assignment results, we give some analysis, estimations and suggestions of the city planning.At last, personal view about the related research area are highlighted after the summary of the whole dissertation.