Research On Multi-mode Bus Scheduling Optimization In Different Scenarios

With the rapid development of urbanization,the traffic congestion caused by the rapid increase of the number of motor vehicles is becoming more and more obvious.Advocating public transport priority is an effective means to alleviate urban traffic congestion.However,most of the existing public transport optimization measures do not start from the actual data and can not be combined with the reality,so they can not effectively improve the public transport operation.Therefore,the application of public transport data to find effective public transport optimization measures has become the key.This thesis studies the collaborative optimization of multi scenario and multi-mode public transport,focusing on the phenomenon of bus bunching,surge passenger flow and random passenger flow.From the perspective of the interests of public transport companies and passengers,a multi-mode combined scheduling method based on different decision criteria is constructed.The research contents are as follows(1)Combined scheduling method of whole bus and short-turning bus for bus bunching phenomenonAiming at the phenomenon of bus bunching caused by road congestion and passenger flow concentration,the congested road sections causing bunching are analyzed,and the passenger flow distribution and inter-stop space-time operation time are analyzed through GPS and IC card data.The combined scheduling strategy of whole bus and short-turning bus is introduced to alleviate the problem of train stringing.Aiming at the road congestion scenario,a multimode combined scheduling optimization model with the goal of minimizing the deviation from the established timetable is established,which can be solved directly by CPLEX after being linearly transformed;Aiming at the passenger flow concentration scenario,a multi-mode combined scheduling optimization model is established to minimize the passenger waiting cost,the operation cost of public transport companies and the bunching penalty cost.Small-scale examples can be solved by CPLEX,and large-scale examples can be solved by simulated annealing algorithm.Based on the case analysis of the real data of Beijing Yuntong 111 line of Beijing Xianglong Bus Co.,Ltd.,the results show that this strategy can reduce the schedule deviation by 43.43% compared with the existing schedule in the case of partial road congestion,so as to effectively alleviate the phenomenon of bus bunching.And reduce the waiting time of passengers by 8.99%;In the scenario of concentrated passenger flow,compared with the existing timetable,this method can completely alleviate the occurrence of bus bunching and reduce the operation cost by 4.72%.(2)Combined scheduling method of customized bus and taxi for surge passenger flowFor the passenger evacuation problem in the scenario of surge passenger flow in large hub stations,the historical total demand of passengers and the restrictions of schedulable vehicles are analyzed,and the quantity decision models of different traffic modes are established to minimize the scheduling cost and penalty cost;Based on the demand quantity of customized bus,an optimization model to minimize the operation route of customized public transport is established.Considering the problem that large-scale examples can not be solved by the existing solution software,the simulated annealing algorithm based on demand splitting is designed.Through the real data analysis of the information of stranded passengers at Beijing Capital International Airport from 23:00 to 24:00,the results show that the proposed combined scheduling strategy can effectively evacuate stranded passengers and optimize customized bus lines while considering passengers' preferences for different transportation modes.(3)Combined scheduling method of whole bus and short-turning bus for random passenger flowFacing the mismatch between passenger flow and vehicle flow caused by random passenger flow,the passenger flow distribution of each group of OD is analyzed through IC data,and the combined scheduling method of whole bus and short-turning bus is introduced to establish a combined scheduling model with chance constrained aiming at minimizing passenger waiting time and operating cost.Based on the analysis of the real data of Beijing Yuntong 128 line of Beijing Xianglong Bus Co.,Ltd.,the results show that under the scenario of random passenger flow,compared with the existing only whole bus operation,when the operation cost is the same,this method can reduce the waiting time of passengers by 24.99%,so that the passenger flow and vehicle flow can be more reasonably matched.The research results of this thesis can be used to guide urban public transport enterprises to formulate effective timetable and organization plan,which has important practical significance for maintaining the healthy and sustainable development of urban public transport.