Why do passengers choose a specific car of a metro train during the morning peak hours

Crowding on metro trains is an important measure of passenger satisfaction and also provides a criterion for determining service frequency and the number of cars necessary for a train set. Particularly in metropolitan areas during morning peak hours, many studies have revealed a considerable difference in the crowding of specific cars on a single train. To accommodate the impact of this phenomenon in calculating metro capacity, a loading diversity factor has been adopted in many transportation studies. However, the underlying causes behind the uneven nature of carriage loading have rarely been examined in a systematic manner. In particular, there has been no trial to explain the nature of choice within a framework for individual passengers. Under the assumption that the uneven selection might stem from each passenger’s intrinsic preference for a specific car, the present study established a nested logit model to investigate the potential factors affecting the choice of a specific car on a train. Passengers were interviewed as they boarded from the platforms of line 7 of the Seoul Metro during the morning peak hours. Results show that the motivation to minimize the walking distance at destination stations turned out to be the most decisive in determining a passenger’s choice for a specific car of a train.

[1]  Maria Johansson,et al.  The effects of attitudes and personality traits on mode choice , 2006 .

[2]  Keemin Sohn,et al.  Separation of car-dependent commuters from normal-choice riders in mode-choice analysis , 2009 .

[3]  Lily Hirsch,et al.  I can sit but I’d rather stand: commuter’s experience of crowdedness and fellow passenger behaviour in carriages on Australian metropolitan trains , 2011 .

[4]  M. Ben-Akiva,et al.  Discrete choice analysis , 1989 .

[5]  Peter Pudney,et al.  Generating Train Plans with Problem Space Search , 2008 .

[6]  Eran Ben-Elia,et al.  The combined effect of information and experience on drivers’ route-choice behavior , 2008 .

[7]  Shlomo Bekhor,et al.  Latent variables and route choice behavior , 2012 .

[8]  Graham Currie,et al.  Quick and Effective Solution to Rail Overcrowding: Free Early Bird Ticket Experience in Melbourne, Australia , 2010 .

[9]  Keemin Sohn,et al.  Increasing the number of bicycle commuters , 2012 .

[10]  Phil Charles,et al.  Managing peak demand for passenger rail: A literature review , 2009 .

[11]  Keemin Sohn,et al.  Optimizing Train-Stop Positions Along a Platform to Distribute the Passenger Load More Evenly Across Individual Cars , 2013, IEEE Transactions on Intelligent Transportation Systems.

[12]  Vukan R Vuchic,et al.  Urban Public Transportation: Systems and Technology , 1981 .

[13]  Dominik Papinski,et al.  Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS , 2009 .

[14]  T Parkinson,et al.  RAIL TRANSIT CAPACITY , 1996 .

[15]  Zhang Qi,et al.  Modeling and simulation of passenger alighting and boarding movement in Beijing metro stations , 2008 .

[16]  Yung-Cheng Lai,et al.  Development and Application of Rail Transit Capacity Models in Taiwan , 2011 .

[17]  Moshe Ben-Akiva,et al.  Discrete choice models incorporating revealed preferences and psychometric data , 2002 .

[18]  Joan L. Walker,et al.  Integration of Choice and Latent Variable Models , 1999 .