Estimation method of passenger trip spatial-temporal trajectory of urban rail transit network and application thereof

Abstract

The invention provides an estimation method of a passenger trip spatial-temporal trajectory of an urban rail transit network. The method comprises the following steps: according to trip state characteristics of passengers in the urban rail transit network, constructing a rail transit super network based on a trip chain, including a network layer, a path layer and a station layer; using WIFI signal data within the scope of the urban rail transit network, and adopting a positioning algorithm based on a received signal strength indication to convert the WIFI signal data into position coordinates of the passengers in the station which are changed over time; based on the correspondence between the position coordinates of the passengers and a station plan, realizing the reduction of walking trajectories in the station; and determining passing stations by identifying the changes in line codes and station codes in passenger position information, and after checking an effective path set in the path layer, realizing the inference of the passenger network travel spatial-temporal trajectory. The estimation method of the passenger trip spatial-temporal trajectory of the urban rail transit network provided by the invention can meet the requirement of positioning accuracy and effectively reduce the walking trajectories of the passengers, and provide a theoretical and technical support for passenger flow analysis, ticket clearing and trip guidance and so on of the urban rail transit network.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and relates to a method for analyzing travel behavior of passengers in an urban traffic system, in particular to a method for estimating time-space trajectories of passengers traveling in a rail transit network. Background technique [0002] In recent years, the transportation system of many cities, especially the urban rail transit system, has entered a new stage of network operation. The increasingly complex network structure has led to the increasing randomness of passenger network travel behavior, and the spatio-temporal distribution of network passenger flow is more complicated and complex. changeable. Understanding passenger network travel behavior and passenger flow distribution rules is the basis for formulating rail transit network traffic organization plans and carrying out station passenger transport organization work, and is an important issue facing the current urb...

AI Technical Summary

Problems solved by technology

Existing related studies mainly use the method of micro-pedestrian simulation to simulate the behavior of passengers in the station, but the simulation method also cannot fully describe the complex travel behavior of passengers, resulting in a large difference between the obtained results and the actual situation.

It can be seen that due to the lack of detailed data in the spatio-temporal dimension, the study of passenger travel characteristics by traditional methods is limited

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