Analyzing crowd dynamic characteristics of boarding and alighting process in urban metro stations

Urban metro system is one of the most sustainable travel modes that affords lots of travel demands in the large cities. The boarding and alighting process is a special form of the bi-directional pedestrian flow through bottleneck, which displays complicated nonlinear dynamics. Quantitatively investi...

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Veröffentlicht in:Physica A 2019-07, Vol.526, p.121075, Article 121075
Hauptverfasser: Qu, Yunchao, Xiao, Yao, Liu, Hao, Yin, Haodong, Wu, Jianjun, Qu, Qiushi, Li, Daqing, Tang, Tao
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Sprache:eng
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Zusammenfassung:Urban metro system is one of the most sustainable travel modes that affords lots of travel demands in the large cities. The boarding and alighting process is a special form of the bi-directional pedestrian flow through bottleneck, which displays complicated nonlinear dynamics. Quantitatively investigating the influence of human behavior on the boarding and alighting process is the challenging problem. To further analyze the crowd dynamics, the surveillance videos at platforms of several urban metro stations in Beijing were recorded, and the time interval of each passenger passing the train door was extracted. According to the extracted individual movement data, the time headway between each two adjacent passengers and the burst size were extracted and analyzed by statistics approaches. The concept of order degree was proposed to describe the activity pattern of a boarding and alighting process. The relationships between these factors including burst size, order degree, and time gap were explored by quantitatively analyzing the individual data. The probability density function of the time headway follows the positively skewed distribution, and the complementary cumulative distribution function shows the property of the power-law distribution. The relationship between burst size and time headway could be divided into three phases. By finding the time gap between the first alighting passenger and the first boarding passenger, the passenger activity under different time pressure was investigated. The obtained individual passenger behavior characteristics could be potentially applied to estimate and design the dwell time and improve the system sustainability. •The individual movement data were extracted to analyze the passenger dynamics.•Time headway between each two passengers shows a power-law tail distribution.•The Levenshtein distance was applied to determine the order degree of a process.•Time pressure of passengers was extracted to describe the activity pattern.•The relationships between the behavioral factors displayed nonlinear characteristics.
ISSN:0378-4371
1873-2119
DOI:10.1016/j.physa.2019.121075