Passengers’ behavioral intentions towards congestion: Observational study of the entry restrictions at traffic bottleneck

Stairs and escalators are usually considered as the commonest bottleneck positions in metro platform. Congestion has taken place constantly due to passengers’ selection behaviors between stairs and escalator, which often cause delays and affect the efficiency of transfer stations. Therefore, this study explores this relationship through the effect of clusters in front of escalator on choice behaviors, by conducting a field observation with varying length of entry restrictions during peak hours. The empirical time data of each passenger entering the stairway or escalator were extracted from the videotapes semi-manually. It was found that proper terrain restraints (certain lengths of fence) could optimize the flow rate pattern of stairway and escalator systems and raise the utilization of stairway, because it reduced conflicts and promoted an orderly movement of the pedestrians in front of escalator according to the analysis of the density of pedestrian flow calculated in waiting area. Besides, the percentage of choosing stairs increased with the density, which was in good agreement with the binary logistic model when the fence was 2 m or 2.5 m long. This study implicates that improvement in service quality of pedestrian facilities need to integrate with entry restrictions on congested bottleneck for effective behavior change. The findings of this study would be helpful for concerned authorities in considering the appropriate attributes of pedestrian facilities for improvement, and other related policy measures to make significant promotion of safe, quick and efficient transport infrastructures.

[1]  Mingjun Liao,et al.  Passenger Traffic Characteristics of Service Facilities in Rail Transit Stations of Shanghai , 2013 .

[2]  Limin Jia,et al.  Effect of Height on Pedestrian Route Choice between Stairs and Escalator , 2014 .

[3]  Jun Liu,et al.  Analysis of subway station capacity with the use of queueing theory , 2014 .

[4]  Eric Wai Ming Lee,et al.  An intelligence-based route choice model for pedestrian flow in a transportation station , 2014, Appl. Soft Comput..

[5]  Julian Hine,et al.  Pedestrian travel experiences: Assessing the impact of traffic on behaviour and perceptions of safety using an in-depth interview technique , 1996 .

[6]  William H. K. Lam,et al.  Pedestrian speed/flow relationships for walking facilities in Hong Kong , 2000 .

[7]  Feng Chen,et al.  Relationship Analysis on Station Capacity and Passenger Flow: A Case of Beijing Subway Line 1 , 2009 .

[8]  F. Eves,et al.  Modelling effects of stair width on rates of stair climbing in a train station. , 2008, Preventive medicine.

[9]  Ming-jun Liao,et al.  Simulation of Ticket Hall Queuing Behavior in Transit Station Based on Cellular Automata Model , 2010, 2010 International Conference on E-Product E-Service and E-Entertainment.

[10]  Goutam Dutta,et al.  Estimating of Capacity of Escalators in London Underground , 2002 .

[11]  Jing Teng,et al.  Passengers' Modal Choice for Vertical Shifts in Metro Stations: Cases from Shanghai , 2012 .

[12]  Dongyan Chen,et al.  Kalman Filtering for Discrete Stochastic Systems with Multiplicative Noises and Random Two-Step Sensor Delays , 2015 .

[13]  Tae Youn Jang,et al.  Direct and indirect effects on weekend travel behaviors , 2009 .

[14]  Serge P. Hoogendoorn,et al.  Pedestrian route-choice and activity scheduling theory and models , 2004 .

[15]  Jie Xu,et al.  Route Choice in Subway Station during Morning Peak Hours: A Case of Guangzhou Subway , 2015 .

[16]  William H. K. Lam,et al.  PEDESTRIAN ROUTE CHOICES BETWEEN ESCALATOR AND STAIRWAY IN MTR STATIONS , 1998 .

[17]  Bin Ran,et al.  A Study on Pedestrian Choice between Stairway and Escalator in Transfer Station Based on Floor Field Cellular Automata , 2013 .

[18]  Jianling Huang,et al.  Simulating on Passengers Coordination with Distribution Service in Railway Station , 2013 .

[19]  Serge P. Hoogendoorn,et al.  Passenger Route Choice concerning Level Changes in Railway Stations , 2005 .

[20]  Dietmar Bauer,et al.  Modelling Random Taste Variations on Level Changes in Passenger Route Choice in a Public Transport Station , 2011 .

[21]  Sun Jinhua,et al.  Analysis of Crowded Degree of Emergency Evacuation at “Bottleneck” Position in Subway Station Based on Stairway Level of Service , 2011 .

[22]  F. Eves,et al.  Investigating behavioural mimicry in the context of stair/escalator choice. , 2011, British journal of health psychology.

[23]  Wang Qi-quan Research on Crowded Stamped Accident Risk at Subway Based on Empowering Related Degree Method , 2013 .

[24]  Takamasa Iryo,et al.  Microscopic pedestrian simulation model combined with a tactical model for route choice behaviour , 2010 .

[25]  David King,et al.  Pedestrian Route Choice of Vertical Facilities in Subway Stations , 2013 .

[26]  William H. K. Lam,et al.  Levels of Service for Stairway in Hong Kong Underground Stations , 2003 .

[27]  Michel Bierlaire,et al.  Discrete Choice Models for Pedestrian Walking Behavior , 2006 .

[28]  Yu Wang,et al.  Stability of a Class of Fractional-Order Nonlinear Systems , 2014 .

[29]  A. Seyfried,et al.  The fundamental diagram of pedestrian movement revisited , 2005, physics/0506170.

[30]  William H. K. Lam,et al.  PEDESTRIAN FLOW CHARACTERISTICS IN HONG KONG , 1995 .

[31]  Dietmar Bauer,et al.  Estimating Pedestrian Movement Characteristics for Crowd Control at Public Transport Facilities , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[32]  Daniel P. Kennedy,et al.  Personal Space Regulation by the Human Amygdala , 2009, Nature Neuroscience.