Study Of The Information Selecting And Processing Problem Of Urban Traffic Flow Guidance Systems

In recent years, with the increasing demands of automobile and freeway usage, the traffic congestion becomes a serious problem. The Intelligent Transportation Systems (ITS) are researched widely so as to solve this problem ultimately. Urban Traffic Flow Guidance Systems (UTFGS) is an important part of ITS, and also is the key technique of execution for ITS.Urban Traffic Flow Guidance System is an active traffic control method, which lead the traffic flow to distribute reasonably by collecting and sending traffic message in real time, so as to reach the effect of utilizing the road network more validly. In this thesis, firstly, the information selecting and processing system based on the License Plate Recognition (LPR) technique scheme is designed, including the selection cell, transmission cell and procession cell. From the software realization angle, the main method and process of procession cell are studied in detail. Secondly, the information processing scheme based on the Extended Kalman Filtering (EKF) state estimation algorithm is studied. The density and speed in multi-segment freeway are estimated in EKF algorithm, and the real travel time computed by the data collected from the LPR equipment is applied to adjust the estimation results. Finally, the thesis presents a number of simulation results via matlab software, which demonstrate that the speed value adjusted is closer to the real speed value.