Modeling And Analyses Of Travel Time Estimation Using Timed Colored Petri Nets

Advanced Traveler Information System, ATIS, has become a research focus at home and abroad in the field of transportation. It can not only predict the travel time of the vehicle accurately, but also control and coordinate the traffic flow on the road network efficiently. As a result, it brings much convenience to the travelers. The thesis has taken a full consideration of the features that the urban trunk road and the traffic flow show. On the basis of it, the thesis built a model to predict the travel time of the vehicle using the time colored Petri nets by analyzing and comparing the current domestic and overseas research status. The main contents are:1.The thesis gave an introduction of the traditional algorithms on the prediction of the travel time of the vehicle through analyzing the existing research achievements. Aiming at the distribution and concurrence features of the urban traffic system, the thesis choose the time colored Petri nets to build the model of it modularly hierarchically, including the road submodel, intersection submodel and the signal control submodel.2.In the urban road network, the efficiency of the vehicle’s passage rate in the intersections is low, and the traffic signal controlling strategy can’t be able to adapt to the variation of the traffic flow on the road. In order to solve these, a signal control optimization algorithm of the road intersection based on the TCPN was proposed. The algorithm’s target is to minimize the number of vehicles in the input section. In order to realize the self-adapted signal control, the algorithm needs to detect the total vehicle number on the section, and then gets the solution of it combining the Matlab.3 On the basis of the TCPN model of the urban road network and the optimized signal controlling algorithm, a fuzzy reasoning method based on the vehicle urgent degree and the density of the traffic flow was proposed by using the TCPN data of the model programmed by the CPN ML language and the operating data of the model acquired through the status monitor. The method can estimate the average speed of the vehicle on the free travel road. As a result, the method can complete the prediction of the vehicle travel time. The thesis also did the simulation and the analysis of the predicting process in cooperation with the Matlab.