Research Of Traffic Choice Mode Based On Fuzzy Order Method

With the rapid development of economy and the increasing of urban population and cars in our country, the per capita car ownership has also rose sharply. Because the construction of the transportation infrastructure can’t traffic demand under the limited urban area, the urban traffic congestion problems are increasingly serious. And a series of social and environmental problems caused by traffic congestion problems is restricting the sustainable development of the city, so the traffic congestion problem has become an urgent problem in the urban development. Transportation demand management can ease the pressure of road congestion and improve the traffic environment through the development and implementation of policy from the origin of inhibition of traffic demand. How to predict the residents travel demand correctly is one of the transportation demand management strategy’s keys. This paper explore the traffic mode choice from the travel of residents attribute. It is one of the key means to solve the traffic congestion, and also can provide a scientific basis for the development of urban transport optimization policies. Follows:First, it mainly describes the research status on the traffic mode choice of urban residents, and points out the existing problems. In addition, the main contents of this paper are also briefly introduced.Second, in order to explore travel attributes influence on traffic mode choice from travel attention point, the multi-objective fuzzy attribute model was established for different travelers, and the traffic mode and travel attention point mutually corresponding fuzzy close degree decision matrix are obtained by fuzzy methods.Considering the travelers’ ages, careers, trip purposes, and other factors, all kinds of travelers’ travel attention point weights and close degrees are obtained by using triangular fuzzy numbers. The traffic order values are obtained and travelers get the preferred traffic mode by constructing the fuzzy order choice mode and using the average area to conduct the comprehensive evaluation of various traffic modes. The example indicates that in range of the bicycles’ attraction, all types of travelers preferred traffic mode was the bicycle; in range of the walking attraction, all types of travelers preferred traffic modes were the walking and bicycle; outside the scope ofthe bicycles’ attraction, below 35 years old and over 60 travelers, bus or subway was the first choice, 36 to 59 years old travelers preferred transportation was private cars.The decision-making process of the choice of traffic mode was simulated by the fuzzy method, and reflecting the process of thinking, the research of model could provide the basis for urban traffic structure optimization and transportation policy strategy.Third, in order to investigate changes of the travel mode choice because of the congestion charging. According to different travel attributes and natures of travel targets, and combining with the travelers’ ages, careers and incomes, the travels’ comprehensive evaluation matrix and comprehensive evaluation values of the travel modes are obtained by the fuzzy method. The disturbance of the congestion charging to the economy target and the comprehensive evaluation of the traffic mode, after the congestion charging are obtained through dealing with the perception degrees of travels to the congestion charging. The order values of the travel modes are obtained by using the mean sort method, and the disturbance of the traffic mode is discussed through the changes of congestion charging. The examples show that the disturbance of the congestion charging to public transport and bicycles are positive, and to private cars are negative. The congestion charging is not the higher and the better, and the best congestion charging level is 10 to 15 yuan. We suggest the traffic management departments to take the best congestion charging. It can improve urban traffic congestion and transport infrastructure in the traveler acceptable range. And it gives certain subsidies to public transport, and makes the congestion charging regimes effectiveness maximizes.At last, it summarizes the work done in this paper, and puts forward the paper’s innovation. At the same time, it gives some improvement in the paper, and points out the direction for the future work.