Intelligent Metro Passenger Flow Monitoring and Guidance System
DOI:
https://doi.org/10.54097/77b3jt62Keywords:
Smart Subway, Multi-terminal Acquisition, Data analysis, Intuitive Guidance.Abstract
With the rapid development of big data, image analysis technology, and artificial intelligence, the related businesses of smart subways have been gradually realized. Facing the huge passenger flow during peak hours, how to guide passengers to relatively spacious compartments has become a hot issue of concern. This article utilizes big data processing and existing image analysis technology in combination with the original subway system to develop an intelligent subway passenger flow monitoring and guidance system. This system consists of three parts: multi-terminal collection, data analysis, and intuitive guidance. The system has the advantages of high reliability, low cost, and real-time guidance, which is expected to help improve passengers' ride experience and ensure the normal operation of the subway.
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Xu J, Li X. Crowded treading warning system for urban rail transit stations based on video detection technology[C]//IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2021, 787(1): 012176.
Yang X, Yang Y, Li Y, et al. Path planning for guided passengers during evacuation in subway station based on multi-objective optimization[J]. Applied Mathematical Modelling, 2022, 111: 777-801.
Gillich K. Dynamic Passenger Guidance in Rail Transport-Decision-Making Behaviour of Passengers[J]. Transportation Research Procedia, 2020, 48: 1450-1465.
Ding X, Liu Z, Xu H. The passenger flow status identification based on image and WiFi detection for urban rail transit stations[J]. Journal of Visual Communication and Image Representation, 2019, 58: 119-129.
Lei Y, Lu G, Zhang H, et al. Optimizing total passenger waiting time in an urban rail network: A passenger flow guidance strategy based on a multi-agent simulation approach[J]. Simulation Modelling Practice and Theory, 2022, 117: 102510.
Zhou M, Ge S, Liu J, et al. Field observation and analysis of waiting passengers at subway platform—A case study of Bei**g subway stations[J]. Physica A: Statistical Mechanics and its Applications, 2020, 556: 124779.
Ding H, Di Y, Zheng X, et al. Passenger arrival distribution model and riding guidance on an urban rail transit platform[J]. Physica A: Statistical Mechanics and Its Applications, 2021, 571: 125847.
Kim J, Madeira-Revell K, Preston J. Promoting passenger behaviour change with provision of occupancy information to help moderate train overcrowding: A cognitive work analysis approach[J]. Applied ergonomics, 2022, 104: 103801.
Li W, Zhou J. The optimize management of passenger organization in transfer station based on dynamic passenger flow analysis[J]. Procedia-Social and Behavioral Sciences, 2013, 96: 1322-1328.
Guo K, Zhang L. Simulation-based passenger evacuation optimization in metro stations considering multi-objectives[J]. Automation in Construction, 2022, 133: 104010.
Liu J, Chen X. Simulation of passenger motion in metro stations during rush hours based on video analysis[J]. Automation in Construction, 2019, 107: 102938.
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