Research On Fare Optimization Of Urban Rail Transit Based On Elastic Demand

With the rapid process of urbanization, traffic congestion and environmental problems are becoming more and more prominent. Compared with other transportation modes, urban rail transit is a new arising transportation mode and it has a lot of advantages such as high-speed, more-safety, more punctual, large capacity, less energy-taken and low pollution. Therefore, many middle and big cities have become to realize that developing urban rail transit with large capacity is a new effective choice to alleviate traffic congestion. In the process of urban rail transit construction and development, a reasonable fare structure or strategy is not only on the matters of the government’s and citizens’ interests, but also concerns the revenues of the urban rail transit operator and the development of the urban rail transit. For this reason, researches on fare design of the urban rail transit have great positive and practical significance.This thesis researches on the urban rail transit fare level under different fare system; proposes a URT fare optimization model considering elastic demand and URT passenger flow assignment; analyzes the optimal fare level,passenger flow and revenue under flat fare,OD-based metered fare and path-based metered fare,then gives some advice on the urban rail transit fare designing. The main work of this thesis includes the following aspects:1. Analyze and summarize the relevant theory about urban rail transit fare designing. The paper enumerates several pricing strategies of urban rail transit of major cities at home and abroad, and expounds domestic and overseas pricing theories’and pricing models’status of urban rail transit. It not only summarizes the pricing theories, pricing strategies, pricing models, but also the fare patterns and their related influential factors.2. Describe the urban rail transit network and propose a stochastic user equilibrium model. According to the operating features and description of the urban rail transit, a network is built to analyze the path composition and it’s generalized cost in the URT network and put forward a stochastic user equilibrium assignment model (SUE) based on elastic demand.3. A bi-level programming model of urban rail transit fare optimization is built and an example is given to illustrate it. Considering the URT elastic demand and government’s role in the fare design, we propose a bi-level programming model of urban rail transit fare optimization with the objective of revenue maximization of the URT operator on the basis of SUE model. An algorithm is also developed to solve the model. To better illustrate the bi-level programming model and it’s application, a numerical example of Beijing URT network is given. According to this example, we obtained the optimal fare levels under different fare structures including flat fare, OD-based metered fare and path-based metered fare, analyses sensitivity of fare level and relevant parameters based on optimal fare solution are given. In the end, we propose some advice on the urban rail transit fare designing by copmparing different fare strategies under fare strategy evaluation indexes.