Research On Passenger Flow Control Of Urban Rail Transit Based On Optimal Matching Of Demand And Supply

Urban rail transit has become the main transportation mode for urban residents traveling as its advantages of high efficiency,large capacity and punctuality.However,the continuous increase of passenger flow demand during peak hours brings pressure to the rail transit system.The problem of passenger congestion in urban rail transit system caused by the mismatch between passenger demand and transport supply capacity is becoming increasingly prominent,which brings potential accident risks to the safe operation of rail transit system.It is necessary to explore the passenger flow control strategy that can solve the problem of passenger flow congestion for the rail transit system.Based on this,multi-level passenger flow control strategy and robust passenger flow control strategy are studied respectively in the optimization of passenger flow control strategy on demand-side,the passenger flow control strategy of joint train timetabling optimization is studied in the collaborative optimization of train timetabling and passenger flow control strategy on the demand-supply cooperative side.By implementing the optimal passenger flow control strategy solved by the model and algorithm,the goal of optimal matching between transportation demand and supply is realized.The main content including four aspects are studied as follows:(1)Research on the theoretical system of matching demand and supply of urban rail transitDefining the meaning of transportation demand and supply,and analyzing the matching mode of rail transit demand and supply under two conditions of stable supply capacity and adjustable supply capacity on the basis of analyzing the causes of the contradiction between transportation demand and supply matching.To achieve the matching goal of demand and supply under corresponding conditions,the optimization strategy set of demand and supply matching is established from the demand side,supply side and demand-supply cooperative side respectively.It lays a theoretical foundation for the follow-up research on the matching strategy of demand and supply,and clarifies the research content of this paper: the optimization of passenger flow control strategy and the coordinated optimization of train timetabling and passenger flow control strategy.(2)Passenger flow control strategy optimization on the demand-side: Multi-level passenger flow collaborative control research considering passengers’ psychological needs.Considering the dynamic characteristics of passenger flow,a multi-level passenger flow collaborative control strategy combining station entrance control and station hall control is proposed for rail transit lines with over-saturated passenger flow.To meet the safety,comfort,timeliness and uncertain information attention needs for passengers,the multi-stage passenger flow cooperative control model is constructed with the passenger flow control strategy under each control level as the decision variable,with the safety capacity of the key area of the station and the maximum passenger capacity of the train as constraints,and optimized to minimize the sum of passenger waiting time in each area of the station of the given weight coefficient.The model is solved by the designed control level automatic judgment algorithm.Taking Beijing Batong line as an example,the numerical experiments of two different scale passenger flow scenarios are carried out.The experimental results show that the multi-level passenger flow collaborative control method combined with station entrance control and station hall control has a good effect on ensuring passenger travel safety,improving passenger efficiency and the waiting environment,and meets passenger travel requirements for safety,comfort and timeliness.At the same time,by adjusting the weight coefficient of the objective function,the waiting time in the uncertain region of passengers’ perception of waiting time is adjusted to meet passengers’ demand for reducing uncertainty information.(3)Robust passenger flow control strategy optimization on the demand-side:Research on robust cooperative passenger flow control considering stochastic characteristics of passenger flow.Considering the dynamic stochastic characteristics of rail transit passenger flow demand,poisson process based on discrete time interval is used to quantify the multiscene random dynamic passenger flow.Aiming at the rail transit line with over-saturated passenger flow under the short turning operation environment,a robust passenger flow control strategy combined with passenger management rules considering the OD of passengers inside and outside the short turning zone was proposed.The model is constructed taking robust control strategy and the actual control strategy as decision variables,taking the maximum passenger capacity of the train and the coupling of each scene as the constraints,and taking the average waiting time minimization of all passenger flow scenarios in the multi-scene passenger flow set as the objective.The linear programming algorithm is used to solve the model.A numerical experiment is carried out on Beijing Fangshan Line.The experimental results show that the robust passenger flow cooperative control method combined with the passenger management rules can not only prevent passengers from crowding on the platform and ensure passengers’ travel safety under the premise of basically not affecting passengers’ travel efficiency,but also provide a passenger flow control scheme with strong applicability for rail transit system.(4)Collaborative optimization of train timetabling and passenger flow control strategy on the demand-supply side: Study on passenger flow cooperative control based on train timetabling optimizationConsidering the influence of train timetabling changes on passenger flow control strategy,a cooperative passenger flow control strategy based on joint train timetabling optimization was proposed for rail transit lines with over-saturated passenger flow under the short turning operation environment.Taking headway and passenger flow control strategy as decision variables,and considering the constraints of train timetabling and maximum passenger capacity,an integer nonlinear programming model is established to minimize passenger waiting time.The model was decomposed into two sub-models which were easy to solve,and a heuristic algorithm combining tabu search and linear programming was designed.Taking Beijing Fangshan Line as an example,the numerical experiment results show that passenger flow control strategy based on joint train timetabling optimization can effectively alleviate the situation of passengers gathering at the platform,greatly improve the travel efficiency of passengers,and provide theoretical support for the safe and efficient operation of rail transit.This paper contains 58 figures,23 tables and 130 references.