Bus IC card passenger get-off station derivation method based on multi-source data

Abstract

A bus IC card passenger get-off station derivation method based on multi-source data has accuracy, effectiveness and operability, can be widely applied to bus OD derivation, and provides theoretical and method bases for analyzing line passenger flow distribution, determining departure shifts and the like. The method comprises the following steps: (1) making basic data preparation: preprocessing original data to obtain effective bus GPS data and IC card swiping data, calculating a bus arrival time table, and counting people getting on a bus at each station; (2) deriving get-off stations based on a commuting travel chain: identifying the commuting travel chain, deriving commuting crowd get-off stations, and counting people getting off at each station; (3) deriving get-off stations based on acommon trip chain: identifying the common trip chain, deriving get-off stations according to the characteristics of the trip chain, and counting people getting off at each station; and (4) deriving get-off stations based on the station attraction weight: defining a station attraction weight calculation method, and calculating the get-off probability of each station from the perspective of gathercounting, thereby obtaining the number of people getting off at each station.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, and relates to a method for deriving bus IC card passenger alighting stations based on multi-source data. Background technique [0002] In the context of the era of big data, mining massive data by means of information technology and extracting effective information from it to support decision-making has achieved good applications in various fields. In the field of transportation, as the data collection and processing methods of traffic big data become more and more mature, it has become a research hotspot to obtain the bus OD matrix based on multi-source data and analyze the distribution characteristics of bus passenger flow. [0003] Multi-source data includes bus GPS data, IC card swiping data, static bus data, etc. Nowadays, the bus IC card automatic toll collection system is popular across the country, and bus vehicles are also generally equipped with on-board GPS devices. The resul...

AI Technical Summary

Problems solved by technology

[0004] At present, most of the bus systems adopt the one-ticket system, that is, to swipe the card when getting on the bus, and not to swipe when getting off, so it is impossible to obtain the passenger alighting information. Therefore, the derivation of the alighting station is the core of mining multi-source data and is also a technical difficulty, and its derivation accuracy is extremely high. OD derivation results of the influence of land on bus passenger flow

Previous research derivation ideas are mainly divided into derivation based on travel chain assumptions and calculation of alighting probability based on site attraction power. The former does not have a high proportion of multi-source data mining, and the latter cannot obtain specific passenger travel trajectories for verification as an aggregate method. accuracy

Images