Users’ Path Choice Analysis Based On Time-based Tradable Mobility Permits

As people’s living standards improve, the number of private cars has greatly increased,traffic congestion has become more and more serious, it has become one of the large st problem for medium-sized cities around the world, which is urgently to be solved. As the growing number of cars’ ownership has become significantly higher the road construction ability and the existing way of traffic demand management(TDM) of car travel restrictions still have its limitations, the economic means of congestion charging to reduce car travel has become a necessary method. However, simply charging for the congestion fee is difficult to be accepted by public, while the money flows is not transparent is also another obvious problem. From above analysis, tradable mobility permits theory arises in this situation. Tradable mobility permits(TMP) theory is more acceptable by public and it can effectively al eviate the problem of traffic congestion.We analyses urban road traffic congestion‘s discriminant methods, causes, impact factors and the ways to ease traffic congestion. Among all of the methods, congestion charging is an effective way to decrease traffic volume, but it also has some drawbacks. So we analyzed its advantages and disadvantages based on the application of congestion pricing theory to improve the shortcoming of traffic congestion pricing theory, TMP as a more reasonable theory has been put forward.After the definition of TMP is defined, applicable conditions, credit control, trading system and regulatory security measures of Tradable mobility permits are detailed analysis. Then we analyzed the bottleneck model and user equilibrium & market equilibrium model, on the basis of the two models, we set users’ need to choose their path and the destination time through the trading platform before they travel, and the charging credit will be different as the road sections various. We call this project as Time-based Tradable Mobility Permits(TTMP). The composition factors such as initial distribution, distribution of quota control, market platform of TTMP is elaborate discussed as well.Due to the implementation of the TTMP will have impact on users’ path choice, we make an analysis to the impact factors of users’ path choice, and established an optimal path choice model in view of the time-based tradable mobility permits. K shortest-path algorithm is employed to solve the model. In addition, if we just set unified parameters in the model to choose a path, the result will be certainly irrationality. So we use the fuzzy evaluation method to solve the model further, and get the path choice scheme of different users, which could meet their needs.Finally, we use TransC AD software to make quantitative analysis of the influence of road network example, time-based tradable mobility permits is employed in the example, and we determine the charge amount of credits by the influence of setting different flow parameters on the road. Then the user’s path matrix is calculated through fuzzy evaluation method, from which we get the optimal path of different users. Compared to the situations that do not use the TTMP method, the user’s travel time and travel cost are greatly reduced...