Method for determining state of passenger flow at local congestion points at transit station

Abstract

The invention provides a method for determining the state of passenger flow at local congestion points at a transit station. The method includes the following steps: deploying WiFi probes at congestion points at a transit station; real-time acquiring the WiFi data of respective wireless communication terminals within a detection range and transmitting the WiFi data to a server; establishing a fingerprint identifying database; using the fingerprint identifying database to perform wireless inter-station positioning and screening the wireless communication terminals, acquiring a wireless optimized communication group; establishing an artificial intelligence matching model; processing the acquired WiFi data of the wireless optimized communication terminal group by using the artificial intelligence matching model, acquiring matched passenger flow; on the basis of the matched passenger flow, computing the traffic capacity utilization rate; comparing the traffic capacity utilization rate and a preset grade standard, acquiring the result of determining the state of passenger flow; and outputting the result of determining the state of passenger flow to an objective terminal. According to the invention, the method herein has the advantages of high accuracy and strong effectiveness.

Description

technical field [0001] The invention relates to the field of rail transit, in particular to a method for judging the state of passenger flow at a local congestion point of a rail station. Background technique [0002] With the rapid development of social economy and the continuous expansion of the scale of rail transit network, the total passenger flow of urban rail transit continues to grow. The earth has increased the potential safety hazards in the operation of the station. [0003] The main passenger flow monitoring and management methods of existing rail transit and their defects are as follows: (1) Through the rail transit automatic fare collection system (AFC system), the passenger flow of each gate entering and leaving the station is obtained to determine the passenger flow status. The main defect is: AFC data With hysteresis, the data detected by AFC can only be output to the vehicle control room with a delay of half an hour, and the AFC data cannot obtain paramete...

AI Technical Summary

Problems solved by technology

[0002] With the rapid development of social economy and the continuous expansion of the scale of rail transit network, the total passenger flow of urban rail transit continues to grow. The earth has increased the safety hazards in the operation of the station

[0003] The main passenger flow monitoring and management methods of existing rail transit and their defects are as follows: (1) Through the rail transit automatic fare collection system (AFC system), the passenger flow of each gate entering and leaving the station is obtained to determine the passenger flow status. The main defect is: AFC data With hysteresis, the data detected by AFC can only be output to the vehicle control room with a delay of half an hour, and the AFC data cannot obtain parameters such as the behavior time of passengers in the station, so it is impossible to determine the passenger flow status at congestion points such as escalators and platforms; (2) use The shortcomings of station video monitoring to judge passenger flow status are: high manual labor intensity and lack of unified quantitative judgment standards; (3) station staff subjectively judge passenger flow status based on historical work experience. With experience, the efficiency and accuracy of decision-making cannot be guaranteed, and the ability to deal with unknown experience events is lacking

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