Urban Rail Transit And Bus Coordination And Optimization Study

Currently, the speed of urban development and traffic pressure are increasing heavily. Public transport as an efficient, environmental and sustainable mode of transport attracts great attention by managers. However, it can only serve the passengers around the sites within walking distance. Regular bus has the features of flexibility lines, good accessibility could make up for the lack of accessibility of urban transit and pick up maximum efficiency. Therefore, coordination and optimization this transportation system are very important.A lot of factors need to be considered in coordination and optimization of urban rail transit and regular bus, such as the optimization of sites transfer, lines space, matching operations. This article from the sites and the lines two sides of urban rail transit and bus to illustrated the method of optimizating feeder system.This article compares some specific characteristics of two modes of transport modes and describes the functions of positioning and strategy. It defines the concepts and types of rail transport and analysis the evacuation features and determines the sites attraction and adjust thinking.Secondly, this paper studies the sites coordination from macro and micro two sides. At macro level, it establishes the hub standard distance model by Transfer distance and probability. I use the Lingo of linear programming to calculate specific location and get the result. Further, I adjust the result with the actual land and road conditions in program to give the final site plan. At micro level, it presents two design ways, which are linear and bay platforms. As an example of the fourth lines in Xi’an Railway Station, it provides guidance sites coordination programs.Finally, this paper studies the coordination of regular bus lines about the competition and cooperation, spatial relations, and functional characteristics. I establish two target models of feeder highest efficiency and minimum operating costs, and determine the multi-objective optimization Genetic Algorithm ideas. In the form of examples of calculating, encoding the bus lines, choosing optimization, crossover and mutation, I get the optimal route.