A Study Of Bus Dispatching Optimization Method Based On Dynamic Characteristics Of Passenger Flow

In the face of the imbalance between supply and demand in urban transportation,the development of public transportation plays an important role in alleviating urban traffic congestion and improving the efficiency of residents’ travel.In order to improve the level of public transport services and reduce the cost of public transport operations,research on the optimization design of bus dispatching has been carried out at home and abroad.At present,China’s bus departure interval setting and capacity allocation are still in the extensive management level.The contradiction between citizens’ travel demand and bus supply capacity urgently needs to improve the bus dispatching strategy.The rational allocation of transport resources has become one of the key research issues of bus dispatch.The current bus scheduling mode often lacks the analysis and prediction of the passenger flow development trend,and ignores the transition between passenger flow of the early peak and the flat peak,and cannot meet the passenger demand in the convergence stage.In addition,there are few studies on the optimal combination of vehicle models,and the influencing factors such as vehicle selection,road environment,and passenger flow changes are rarely considered in the research scope of multi-vehicle configuration.In order to effectively solve the above problems,this paper elaborates the spatial and temporal distribution characteristics of bus passenger flow according to its dynamic characteristics.On this basis,the dynamic balance characteristics of bus supply and demand are analyzed from the perspectives of passenger demand and capacity supply,providing an important basis for effectively grasping the dynamic development trend of bus passenger flow.Based on this,the investigation content and investigation method of passenger flow characteristics are determined.Since the grey Verhulst model in the grey prediction method is applicable to the sequence with random fluctuation to a certain extent,this paper adopts the grey Verhulst model to predict bus passenger flow.Then,according to the dynamic characteristics of passenger flow,the optimization models of bus departure interval in peak hours and flat peak hours are established respectively,and the genetic algorithm is selected to solve the models,so as to realize the goal of minimizing the weighted sum of bus operation cost,passenger waiting cost and vehicle perception cost.The results of passenger flow prediction and departure interval optimization are introduced into the multi-vehicle configuration of bus routes.According to the influencing factors of bus capacity configuration,a multi-vehicle configuration optimization model with the minimum cost of bus company and line capacity as the objective function is established,and the model is solved by using MATLAB software.Finally,Dalian Bus Rapid Transit is taken as an example to analyze the case.The Dalian BRT Line information and passenger flow data are obtained through investigation and collation.Passenger flow forecasting,departure interval optimization and vehicle optimization configuration are carried out in turn.By comparing and analyzing the operation cost,passenger cost and service level generated by the dispatching and departure plan before and after optimization,the feasibility and practicability of the multi-vehicle optimization configuration scheme proposed in this paper are proved.