Bus passenger flow data collection and origin-destination point analysis method and system

Abstract

The invention discloses a bus passenger flow data collection and origin-destination point analysis method. The method comprises the steps that corresponding WIFI routers are arranged in a bus and a bus stop at the same time, MAC address data of intelligent terminals carried by passengers in the bus and passengers waiting for a bus on the bus stop is detected and collected, and according to the bus door opening and closing signals collected by a bus door signal collecting device, passenger identity confirmation and invalid data filtering are carried out. The invention further discloses a bus passenger flow data collection and origin-destination point analysis system which comprises the vehicle-mounted WIFI router, a bus door signal collecting device, the bus stop router and an MAC identity recognition and confirmation module. Bus passenger flow analysis is carried out based on various data sources, and high accuracy of WIFI identity recognition information for bus passenger flow and OD analysis is ensured.

Description

technical field [0001] The present invention relates to a bus passenger flow data collection and analysis technology, in particular to a method and system for bus passenger flow data collection and OD (Original Destination, origin and destination) analysis based on WIFI identification, vehicle door status and bus IC card data. Background technique [0002] At present, the data collection of bus passenger flow generally adopts the following passenger flow collection methods: 1. Manual follow-up points. The problem with this method is that the manual investment is too large, the data collection cannot achieve full coverage of time and space, and the collected data The accuracy rate is greatly affected by human beings. 2. By installing additional automatic passenger flow statistics equipment on the bus, such as infrared active induction type, video analysis type, pedal type, etc., these solutions can have good detection accuracy when the passenger flow is relatively small, but ...

AI Technical Summary

Problems solved by technology

[0002] At present, the data collection of bus passenger flow generally adopts the following passenger flow collection methods: 1. Manual follow-up points. The problem with this method is that the manual investment is too large, the data collection cannot achieve full coverage of time and space, and the collected data The accuracy rate is greatly affected by human

2. By installing additional automatic passenger flow statistics equipment on the bus, such as infrared active induction type, video analysis type, pedal type, etc., these solutions can have good detection accuracy when the passenger flow is relatively small, but in the vehicle When it is crowded, the detection accuracy will be greatly reduced, and these detection methods know the number of people getting on and off, but it is impossible to know who got on and off the car

3. Based on the statistical method of IC card swiping data and coin data, since many cities use a one-ticket system to get on the bus by swiping the card or inserting coins once, it is impossible to know at which station passengers get off, and it is impossible to prepare for the analysis of passenger flow and OD data

4. Passenger flow statistical analysis based on WIFI identification, such as the patent application number CN201310729845.X, this method also uses WIFI data for passenger flow detection and analysis, but because the coverage of WIFI signals ideally reaches a radius of 100 meters, therefore, This invention does not consider a more effective data filtering method, directly using the scanned WIFI data cannot guarantee the accuracy of the results, and there will be a large amount of multi-inspection data, such as the WIFI data of pedestrians on the roadside at the platform, and the WIFI data of private vehicles around the bus cannot be effective remove

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