Rail Transit Passenger Flow Travel Information Extraction And Analysis Method Based On Cellular Data

As the backbone of urban traffic,urban rail transport is responsible for the main transportation functions of the city.By the end of December 2017,a total of 5021.7 kilometers of urban rail transit lines have been completed in 34 cities,which means the number of urban rail transit lines in China is still increasing.And in 2017,33 new lines were added,representing an increase of 62.5% over the previous year.And daily passenger flow has been exceed more than 10 million in Beijing,Shanghai and other urban rail transit.Faced with such a huge rail transit passenger flow and a complex rail line network,how to improve the level of rail transit services to increase the attractiveness of rail transit has become a key issue in rail transit operations.Refine collecting and analysing the traffic information according to smart traffic technology,operational decision-making basis can be provided to traffic managers.As a kind of transport big data,mobile signaling data has been widely used in various fields of urban transport research with the characteristics of wide coverage,real-time dynamic and low acquisition costs.In this paper,collecting individual travel under different travel path of rail transit data and evaluating the collection effect is carried out based on the cell location technology and handset switching technology,combined with travel log test data acquisition effect assessment.First of all,different individual rail transit travel tests with or without transfer mode was designed in this paper.The traveling individuals carried the normal mobile phones to receive the communication signals and recorded the real travel paths,and then the collecting mobile phone signaling data was compared with the travel log to explore the regularity of the sequence of signaling data generated during the individual rail transit and pave the way for the subsequent algorithm of travel information extraction.Secondly,this paper constructs the method of extracting the travel information of the rail transit passenger flow on the basis of summarizing the shortage of the existing algorithms for recognizing the travel path of the rail transit.It analyzes and extract the passenger’s travel time at the key points such as the inbound,outbound and transfer points in the underground rail transit system,and the place of departure and the destination were also identified in this paper.In the entering-station identification,signaling data generated by different signaling events with location area updating are used to identify key trajectory entering-points based on space-time sequences between adjacent key trajectory points and the location information of the rail transit base station in the leaving-station identification,a method based on the principle of proximity was proposed which combined with the base station information near the orbital station.And the transfer station and intermediate station identification method was raised,based on the spatial and temporal constraints of the inbound and outbound signaling sequence,combined with the information of the adjacent stations in the transfer station;and the travel path of the passenger rail transit was checked based on the space-time constraints.At the same time,analyzing visual analysis for the entering-station and leaving-station passage flow distribution is carried out,based on DBSCAN clustering algorithm to identify the scope of the site services.At this point,the journey from one-day signaling sequence to all passengers on rail transit is completed.The results of the example data show that the travel path of passengers can be accurately and efficiently identified by the recognition process based on the signaling data.The service scope of the station identified by the signaling data is consistent with the characteristics of the passenger flow and the characteristics of the land use around the site,which provides a basis for the further analysis of the characteristics of the outflow traffic of the rail transit.This paper takes the residents’ mobile phone signaling data of Chongqing as the research object,combined rail transit card-swiping data,verify and evaluate the feature extraction effect of rail transit passengers based on mobile signaling.This paper mainly evaluates the temporal and spatial distribution characteristics of entering-station,leaving-station,transfer station and intermediate t station passenger flow in rail transit system,the distribution characteristics extraction results of passenger flow sources and orients at rail transit stations.Finally,the results show that passenger flow characteristic information of rail transit can be obtained accurately according to the phone signaling data and the passenger flow distribution characteristics acquired can meet the nature of land use around the site.