Research On Location Decision And Scheduling Optimization Of Small Flexible Bus For Agent Drivers

The occurrence of traffic accidents will cause serious loss of personal property and social stability,which is an increasingly severe social problem in the world.The WHO accident survey shows that drunk driving is the leading cause of traffic accidents,about 50%-60% of traffic accidents are associated with drunk driving.The agent driving service provides a relatively safe choice for the drunk car owners,is developing rapidly as a new industry that meets the needs of the times and the market.But the peak period of the agent driving is mainly concentrated in the 20:00-3:00,which is the outage time for the bus and subway.And the business district and the residential district are distributed in different areas of a city.After an agent driver has sent a customer,there is no suitable transportation way for him to arrive at the next service place.Under such circumstances,drivers can not provide timely and high quality services in many cases.Flexible bus is a new type of intelligent public transportation service mode between conventional buses and taxis.Through GPS,DIS,ITS and other emerging technologies,flexible bus has a prosperous future.If an enterprise can provide flexible driving buses for driving drivers in the business district and residential area,it can stand out the industry with high efficiency and timely service,and win a higher market share.By processing the driver's previous GPS data,this paper excavates the driver's start service and terminates the service position,and clustering these positions through DBSCAN.The center of space cluster is regard as the location of flexible bus station.The results show that the DBSCAN algorithm has more candidate stations in the central area of the city,and the service of each station is balanced relatively.While K-means clustering algorithm is more concentrated,fewer stations in the city center,resulting in the high service pressure,so this paper selects the DBSCAN clustering results as a site selection scheme.Then,scheduling optimization model is established,and an effective algorithm is designed to solve the problem.Then,this paper establishes the maximum profit model for the dynamic scheduling problem of the flexible bus system.Make an in-depth study on the optimal scheduling scheme to reduce the operation cost and improve the efficiency.Design an improved ant colony algorithm to solve the initial driving of flexible bus.When the new order appears,choose the right vehicle according to the two principles and schedule the route.Finally,Dalian city is selected as the research object.The location gained by DBSCAN algorithm is used to construct the scheduling network.200 pairs of ODs are randomly selected from the previous OD database of the agent driving industry.On this basis,the optimization model of agent driving scheduling is solved,and the dispatched paths are analyzed.And then,for changes in vehicle number,time window and order quantity,this paper makes a sensitivity analysis.Finally,this paper runs the algorithm 10 times,the result verifies the algorithm is of great stability and effectiveness.