Research On Back-temporal Modeling Method For Urban Rail Transit Passengers Based On Travel Time Data

As urban rail transit of china gradually enters the era of networking operation,the topology of the line network become increasingly complex.It provides residents with diversified travel choice and excellent travel experiences,but it also makes the networking passenger distribution increasingly complex,which brings a huge challenge to the operation management of rail transit.Passenger travel time data,which records the starting and ending points of passenger travel and the corresponding time,can describe the passenger travel process to a certain extent,but lacks some information of time nodes.Meanwhile,the travel process of every passenger is limited by many factors,such as their own attributes,train operation conditions and rail transit system conditions.Based on the passenger travel time data,this thesis analyzes and excavates it deeply.Combined with the rail transit train operation data and passenger individual attributes,it focuses on the impact of station detention in peak hours on passenger travel time and travel process,so as to quantify the matching degree of passengers for each train number and path in different time periods and different stations.Finally,it can trace back from travel time to travel time and space path from a micro perspective and provide new research ideas and directions for the calculation of passenger flow distribution of rail transit.The summarization of the research contents of the thesis is described as follows:(1)Analyze the characteristics of rail transportation AFC data and train operation data,disassemble the passenger travel time into several components according to the travel process,and analyze the fluctuation of travel time according to the influencing factors of each part and the actual passenger travel data.(2)Analyze the travel process of passengers at various stages,deeply dig the AFC data to obtain the passenger flow information of the station at different time periods,and propose the concept of passenger detention rate,describing the possibility of passengers not being able to ride normally at the station due to factors such as full train load.Establish the association between passengers and trains,passengers and routes,and realize the traceback from travel time data to specific travel processes.(3)Taking Shenzhen Metro as an actual case,the research method proposed in this paper is applied,and the rationality of the research method is verified in conjunction with the clearance results under the current model.The innovations of this thesis are mainly reflected in:(1)Digging into travel time data,counting passenger travel time fluctuations in different periods,and using the travel time distribution of non-transfer passengers on the same line at the same time to characterize the passenger’s detention at various potential detention points.(2)In addition to the personal attributes of passengers,the effects of external factors such as full train load and station passenger flow conditions on passenger route selection and travel time are emphasized.(3)The concept of passenger detention rate is proposed,and a method for calculating the time-delayed rate of passengers at a station is established,which is used to describe the possibility of detention of passengers who arrive at a station in a certain direction in a certain period of time,and establish the correspondence between passengers and travel plans.