Subway station area passenger flow detection and analysis method based on multi-modal perception capability

By dividing the subway station into a near-field anchoring area and a far-field reconstruction area, and combining the weighted fusion of visual and radio frequency data, the detection error in high-density passenger flow scenarios was solved, and accurate statistics of passenger flow data and environmental adaptability were achieved.

CN121884287BActive Publication Date: 2026-06-09SHANGHAI PENG CHONG INTELLIGENT TECH CO LTD
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Patent Information

Application Number
CN202610343003.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-03-20
Publication Date
2026-06-09
Estimated Expiration
2046-03-20

AI Technical Summary

Technical Problem

In high-density passenger flow scenarios, existing technologies suffer from problems such as video detection leading to missed detections at distant locations due to perspective obstruction, and radio frequency detection causing distortion in passenger flow statistics due to fluctuations in penetration rate, making it impossible to accurately reflect the congestion situation in subway stations.

Method used

By calculating the visual effectiveness coefficient, the near-field anchoring area and the far-field reconstruction area are divided. The near-field visual count and dynamic radio frequency penetration factor are combined to perform weighted fusion of passenger flow data. The near-field visual data is used to calibrate the radio frequency data, adapt to changes in the crowd structure, and correct radio frequency signal errors.

Benefits of technology

It improves the accuracy and environmental adaptability of passenger flow detection in subway stations, solves the problems of remote missed detection and penetration rate fluctuation in high-density passenger flow scenarios, and realizes accurate statistics of passenger flow data.

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Abstract

The application belongs to the technical field of passenger flow monitoring and management, and particularly relates to a subway station area passenger flow detection analysis method based on multi-modal sensing capability, which comprises the following steps: calculating a visual effectiveness coefficient according to the effective vertical distance of a pixel point in a video frame to a near-end reference line, and then dividing the video frame into a near-field anchoring area and a far-field area to be reconstructed; calculating a dynamic radio frequency penetration factor according to the number of passenger targets in the near-field anchoring area and the number of near-field radio frequency terminals; and obtaining a reconstructed passenger flow total amount by using the visual effectiveness coefficient of the far-field area to be reconstructed to perform weighted fusion according to the number of passenger targets in the near-field anchoring area, the dynamic radio frequency penetration factor, the number of far-field radio frequency terminals and the number of passenger targets in the far-field area to be reconstructed. The application can adaptively change the crowd structure, effectively solve the problem of missed detection caused by far-end visual occlusion and improve the passenger flow detection precision.
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