Study On The Method Of Traffic State Identification And Congestion Propagation Estimation For Urban Road

Traffic congestion has been a global problem and makes serious affects on the persistence development of city and living of human beings. It is significant for decision-making of congetion dispersal to find congestion rapidly and estimate congestion propagation trend reliably. This dissertation performed systematic studies on the method of traffic state identification and congestion propagation estimation for urban road. The main research works conclude:(1) Study on the Data Collecting Technology based on GPS Probe VehiclesThe GPS probe vehicles have been a promising technology for traffic information collection detection with the GPS technology widely applied in transportation field. Some parameters settings of the GPS probe vehicles in data collecting will severe affect accuracy and reliability of the traffic information collection, mainly including link-dividing, sampling time interval of GPS data, transmission interval of GPS data, analysis interval of traffic data and probe vehicles sample-size. Considering the accuracy and cost of taffic data colletion, real-time and reliability of traffic state identification, this paper studies the method of special and temporal interval optimizing and the method of the GPS probe vehicles sample size.(2) Study on the Method of Traffic Papameters On-Line EstimationTraffic parameter data is crucial and necessary for traffic state survilliance and control systems. But due to the limitation of cost and actual condition, it is impossible to fix traffic dectectors at any spots, so that it is difficult to obtain the traffic paramters data of all spots. So it is significant important of the traffic parameters on-line estimation. This dissertation adopted Cell Transmission Model design a traffic parameter estimation method, inclue traffic flow, density, occupation and queue length. In order to improve the estimation acuuracy, Kalman Filter Technology was applied into CTM. Analysis results of simulated data showed that the proposed method can be used to on-line estimate traffic parameters of urban road.(3) Study on the Method of Traffic Parameters Dynamic Multi-steps PredictionThe becoming tendency information of traffic parameters is important for the making of traffic management decision and travel decision. The method of dynamic multi-steps traffic parameters prediction was proposed based on similarity searching technology of time series and common prediction method. Then some critical problems were analyzed and discussed, including the prediction steps, length of priminary series and time to searching similar time series. At last, the case study was performed with actual data, the results showed that the proposed multi-steps predition method have nice practicability.(4) Study on the Method of Traffic State Automatic IdentificationIndentifying the traffic abnormal state promptly and accurately is very important for advance the efficiency and effect of traffic manage. First the thesis defines absolute criterion and relative criterion for traffic congestion measure. Second, designed a traffic state indentification method based on GPS data and fixed detector data respectively. And then analysis the affect of probe vehicles sample-size on the reliability of traffic state identification result. Last the simulated data was used to validate the method proposed.(5) Study on the Estimation Method of Traffic Congestion PropagationThe information of the space propagation trend and duration of the traffic congestion are very important for the traffic management to make reasonable and effective measures for disperse congestion. This thesis analyzed the rule of traffic congestion propagation, and put forward the method of traffic congestion propagation estimation for single link and road network, and congestion duration estimation method. Finally, simulated data was used to test the proposed methods.