Modelling the distribution of passengers waiting to board the train at metro stations

Seriani, Sebastián; Fujiyama, Taku

doi:10.1016/j.jrtpm.2019.100141

Cited by 9 publications

(10 citation statements)

References 31 publications

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“…Seriani and Fujiyama [35]; Seriani and Fujiyama [36] Seriani et al [9]; Wu and Ma [37]; Loukaitou-Sideris et al [38] Handrails, barriers, waiting area, yellow safety line (location, length, width) (m)…”

Section: Spatialmentioning

confidence: 99%

“…Seriani et al [8]; Seriani and Fujiyama [36]; Rowe and Tyler [41] Space used by passengers (distance between passengers, area used by passengers) (m o m 2 /passenger) Seriani et al [8]; Valdivieso and Seriani [11] Distribution of passengers, formation of lines of flow, queues (quantity)…”

Section: Spatialmentioning

confidence: 99%

“…Seriani et al [8]; Seriani and Fujiyama [36] Flow of passengers at the doors (passengers/min-m) Fujiyama et al [20]; Fernandez et al [21]; Daamen et al [25] Boarding and alighting time (s)…”

Section: Spatialmentioning

confidence: 99%

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Factorial Design with Simulation for the Optimization of the Level of Service in the Platform-Train Interface of Metro Stations—A Pilot Study

et al. 2022

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Metro stations are considered complex areas of pedestrian mobility due to the increasing congestion, due to the a high level of demand of different circulation spaces. Given this situation and the limited physical spaces remaining to develop transport systems in urban areas, railways acquire greater relevance given the need to mobilize pedestrians. Within the stations, the most problematic area is the platform-train interface (PTI) due to the high number of interactions between passengers boarding and alighting. The objective of this study is to identify the PTI configuration that maximizes the level of service for passengers, safeguards the operational continuity of the system and improves user experience by reducing dissatisfaction and delay times. For this, a pedestrian microsimulation model is used in order to recreate the reality of a generic metro station and its different scenarios given the combinations of two factors: the platform configurations (topology) and the traffic control elements. Subsequently, these scenarios are analyzed through a factorial design, looking for the situation that optimizes the combination of metrics chosen in a weighted way. Finally, it is found that the PTI configuration that maximizes the level of service for users is the mixed station with signaling. It is this which includes the factors with the greatest positive effect on the chosen metrics.

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Section: Spatialmentioning

confidence: 99%

Section: Spatialmentioning

confidence: 99%

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Factorial Design with Simulation for the Optimization of the Level of Service in the Platform-Train Interface of Metro Stations—A Pilot Study

et al. 2022

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“…This would imply, as in other cities such as Buenos Aires [5], that situations of non-compliance with regulations are reached due to crowding levels in the train-platform interface. This space is the most complex to analyze, which has registered a high interaction between passengers getting on and off the trains [6,7]. If the interaction increases the train will maintain at the station for a longer time, due to the time each passenger gets on and off the train [8].…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Effect of Crowds on Passenger Behavior Inside Urban Trains through Laboratory Experiments—A Pilot Study

et al. 2022

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The objective is to study the distribution of passengers inside urban trains for different levels of crowding. The study is carried out through the observation of videos made by laboratory experiments in which a mock-up of a carriage represented the boarding and alighting process. The Fruin’s Level of Service (LOS) was adopted, but with a different approach, in which the train is divided into five zones (central hall, central aisle, side aisle, central seats and side seats). The experiments are based on the behavior of passengers in the London Underground; however, this study could be expanded to any conventional rail or LRT system. For the laboratory experiments, it is proposed to build a metro carriage and a corresponding platform section, and the scenarios will include different levels of crowding of passengers boarding and alighting to produce a variation in the density on the platform. According to the crowding level, the results allow obtaining the distribution and movements generated by passengers in the five zones for different instants of time during the process of boarding and alighting. It is observed that passengers are distributed according to safety and efficiency conditions. For example, passengers tried to avoid contact with each other unless it is inevitable. In relation to comfort, the seats of the carriage are always used even if there is a low level of crowding. If the crowding level increases, the boarding and alighting time go up. In addition, passengers will spend one or two seconds more if the “let’s get off before getting on the carriage” behavior is breached. This kind of experiment can be used in further research as a way to test “what-if” scenarios using this new method of discretization of the space inside the train, which cannot be tested in existing stations due to restrictions such as the weather, variability of the train frequency, current design of the trains, among others. New experiments are necessary for future research to include other types of passengers such as people with disabilities or reduced mobility.

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“…However, there are significant problems of empirical measurements and models because it is not possible to control all the variables (i.e., layouts of station, weather, personality of passengers, etc.) [15].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Walking-Edge Effect in Train Station Evacuation Scenarios: A Sustainable Transportation Perspective

et al. 2019

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Due to the highly developed rail transit over the past decades, the phenomena of complex individual self-organized behaviors and mass crowd dynamics have become a great concern in the train station. In order to understand passengers’ walking-edge effect and analyze the relationship between the layout and sustainable service abilities of the train station, a heuristics-based social force model is proposed to elaborate the crowd dynamics. Several evacuation scenarios are implemented to describe the walking-edge effect in a train station with the evacuation efficiency, pedestrian flow, and crowd density map. The results show that decentralizing crowd flow can significantly increase the evacuation efficiency in different scenarios. When the exits are far away from the central axis of the railway station, the walking-edge effect has little influence on the evacuation efficiency. Obstacles can guide the movement of passengers by channelizing pedestrian flows. In addition, a wider side exit of the funnel-shaped corridors can promote walking-edge effect and decrease the pressure among a congested crowd. Besides providing a modified social force model with considering walking-edge effect, several suggestions are put forward for managers and architects of the train station in designing sustainable layouts.

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Modelling the distribution of passengers waiting to board the train at metro stations

Cited by 9 publications

References 31 publications

Factorial Design with Simulation for the Optimization of the Level of Service in the Platform-Train Interface of Metro Stations—A Pilot Study

Factorial Design with Simulation for the Optimization of the Level of Service in the Platform-Train Interface of Metro Stations—A Pilot Study

Analyzing the Effect of Crowds on Passenger Behavior Inside Urban Trains through Laboratory Experiments—A Pilot Study

Analysis of Walking-Edge Effect in Train Station Evacuation Scenarios: A Sustainable Transportation Perspective

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