Traffic Congestion Evaluation And Measurement Based On Probe Vehicle

Traffic congestion becomes more and more serious with the rapid development in modern society. Traffic management and control are aimed to avoid traffic jam and give effective solution of releasing transportation pressure, which is the key function of Intelligent Transportation System (ITS). Therefore, it is important to detect and estimate the traffic congestion. With the evaluation result of traffic congestion in advanced traffic information system, traveler may find the best way against traffic jam, and traffic managers can be benefited by such historical data analysis in layout of city road nets.In the thesis, with the analyzing of traffic congestion causes, many methods to evaluate traffic jam are reviewed, from which, Level of Congestion (LOC) is defined as an index to describe a continuous traffic processing from free flow to traffic jam. LOC should also be of coherence with human perception on traffic congestion. According to the relationship between characteristics of the traffic flow and traffic congestion, fuzzy logic is adopted to partition the basic parameters (mean velocity and flow volume) into several fuzzy subsets, then fuzzy inference system is established to generate LOC.To test the feasibility of LOC and fuzzy inference system, a simulation tool is used to collect the data of traffic flow and visually evaluate the traffic congestion by people. Two methodologies are used to obtain the system model. One is fuzzy identification based on the least mean square method and the other is based on adaptive neuro-fuzzy inference system. As a result from fuzzy inference surface analysis, LOC can be supported by the fuzzy inference system and can recover human's general perception on judging congestion.In the last section, probe vehicle system is discussed as a means of data collection. The framework and detection process of probe vehicle system are depicted. Particularly, GPS data processing and traffic parameter evaluationbased on probe vehicle reports are developed. A method to judge the type of traffic congestion is studied, and according to the previous result, the step to calculate LOC in the type of non-recurrence congestion is finally presented.