Research On Bus Line Network Optimization Model Based On Passenger Flow Count

Giving priority to the development of urban public transport is an important way to build a resource-saving and environment-friendly society.The optimization of bus routes can increase passengers' riding experience and save the cost of public transportation companies.It is one of the important measures for achieving fine management of public transportation.Many scholars have carried out a lot of research on the optimization of bus routes,and the bus passenger flow is one of the important parameters.The traditional data collection is based on the statistical value of manual investigation or experience,and the passenger flow data is accidental and inaccurate.At present,some cities have deployed the bus passenger flow counter,which can collect the traffic data of high precision(>=95%).Therefore,this thesis proposes a research on the optimization model of public transit network based on passenger Flow Count.On the basis of the research on existing bus network optimization model,Firstly,This thesis carries out probabilistic analysis of the residents' travel patterns,proposes an OD matrix generation model based on the passenger flow count,and validates the model with actual survey data.The results show that a more accurate OD matrix can be obtained through this model.At the same time,this thesis studies the distribution forecast of bus trips,and proposes a bus travel distribution forecasting model based on improved gravity model.Secondly,based on the realtime data generated by the passenger flow counting device and the research ideas of the solution method,a multi-objective public transit network optimization model based on passenger flow counting is proposed in this thesis.The model aims at optimizing the daily average full-load rate of the line network and the highest direct passenger rate,and converts the multi-objective problem into a single-objective problem with a linear weighted method.Finally,based on the improved ant colony algorithm,this thesis solves the optimization model of the public transit network,finds the route with the largest objective function value under constraint conditions,and proposes an optimization adjustment method based on the current public transit network.The thesis is based on the passenger flow data collected by the bus passenger flow counter installed on the bus in Xi'an,and uses the improved ant colony algorithm to simulate the selected area.The simulation results show that using the improved ant colony algorithm to solve the multi-objective public transportation network optimization model proposed in this thesis has achieved a good optimization effect and has certain practical significance.