Micro-behavior Analysis And Simulation Of Passenger On Urban Rail Transit Platform

As a key part of the modern urban transportation system,the urban rail transit system is experiencing rapid development in major cities of China in recent years,and gradually becoming a guarantee for daily travels of residents.With the advancement of society and economy,the travel activities of urban residents have increased significantly,along with the volume of passenger flow in rail transits.The fastgrowing passenger flow has become one of the major pressures faced by rail transit stations,especially in megacities such as Beijing and Shanghai.Under the impact of massive passenger flow during peak hours,rail transit platforms are prone to form uneven distribution of passengers and queue-skipping behaviors,and even collisions and fights among passengers,which will eventually lead to issues such as low passenger boarding efficiency,disordered boarding of passengers,and train delays.In addition,the massive passenger flow may also induce inefficient exit of passengers and considerably increase the likelihood of safety accidents.Therefore,it is imperative to optimize the daily operation and emergency management of rail transit stations with the aid of improved informatization,which can provide regional and refined guidance for passengers in the station,and therefore comprehensively improve the quality of services at the stations.Based on the aforementioned problems,this thesis investigates the characteristics of passenger behaviors at urban rail transit platforms based on the existing studies about the uneven distribution of passengers,disordered passenger queuing,and chaos during the exit process.Three microscopic pedestrian models considering the waiting area choice behavior,boarding decision-making behavior,and exit choice behavior of passengers on the platform are developed,respectively.Based on the simulation models,we study the key impact factors and decision-making mechanisms of passenger behaviors.These models can provide theoretical guidance and decisionmaking reference for the accurate management and passenger guidance of populated rail transit stations.The main contributions of this thesis can be divided into the three aspects as follows:(1)For the investigation of the waiting area choice behavior,firstly,we abstract the behavioral preferences of passengers such as nearest-first boarding,farthest-first boarding via video calibration,and choose passenger,platform and immediate environment as the key impact factors of choice behavior.Secondly,we employ questionnaire investigation and factor correlation analysis to identify the key factors of passenger waiting area selection,and obtain the key factors that affect the passenger waiting area selection behavior: walking distance,passenger aggregation,queuing space,carriage full rate,and passengers’ familiarity with the station.On this basis,the attractiveness model of the waiting area is constructed,and a simulation model of passenger waiting area selection behavior based on cellular automata(CA)is established.The influence mechanism of the arrival rate of passenger flow,the distance of passengers to the waiting area,the aggregation degree of passengers in the waiting area,and the influence coefficient of the available queuing space in the area to the utilization rate of the waiting area are investigated.Approaches of improving the utilization rate of the waiting area are discussed.To excavate the influence mechanism of different factors on the utilization rate of the waiting area,to support the formulation of the passenger guidance strategy and refine the organization of the passenger flow.(2)A simulation model of passengers’ decision-making behaviors based on cellular automata is constructed at rail transit platform,which comprehensively considered the behavior of queuing and boarding,queue-jumping and postponing boarding due to queue-waiting short-turning subway,aiming to reveal the influence mechanism of different behaviors on passengers’ boarding efficiency.The choice process of passengers from entering the platform to entering the carriage is defined as the passenger’s decision-making behavior.It is a complex dynamic process formed by two stages: queueing and boarding.The second research aspect of the thesis focuses on the analysis of the queuing and boarding behavior.Firstly,considering the waiting behavior of passengers caused by the train intervals and other reasons,a decisionmaking model for passenger boarding based on the interaction between passenger tolerance and compartment saturation is established.Then,considering the queueing behavior of passengers on the platform,a passenger queuing choice behavior model is established according to the diverse characteristics of passenger queueing behavior.On this basis,based on the cellular automaton(CA)method,a simulation model of passenger boarding decision-making behavior on the platform is constructed,and the passenger boarding efficiency under different passenger flow characteristics is simulated and analyzed,the Influencing mechanism of the boarding efficiency is investigated.This research can provide reference and support for the accurate organization of waiting passengers on the platform and the formulation of control policies to improve the efficiency of passenger boarding.(3)Based on the in-depth analysis of the exit selection behavior characteristics of the passengers in the massive passenger flow related scenarios,a simulation model of the exit selection behavior of passengers under the influence of the distance of the exit path,the dynamic congestion degree and the speed of other passengers is constructed.Firstly,a microscopic pedestrian simulation model is constructed according to the characteristics of passengers’ exit choice behavior.The threshold of changing exit intention and information release period time are calibrated to ensure the validity of the passenger exit choice behavior model.On this basis,considering the factors such as exit congestion,passenger flow speed,platform layout,three exit strategies are proposed under the combination of factors such as the distance of the egress path,the dynamic congestion degree and the speed changes of other passengers on the path.The exit efficiency under different exit strategies is simulated and evaluated,and the optimal passenger flow density and the corresponding exit induction strategy under the exit situation are determined through the analysis of simulation results.The research results can provide theoretical guidance and simulation tools for the formulation and optimization of urban rail transit platform passenger exit strategies.