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Models of bus boarding and alighting dynamics

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  • Sun, Lijun
  • Tirachini, Alejandro
  • Axhausen, Kay W.
  • Erath, Alexander
  • Lee, Der-Horng

Abstract

Understanding the dynamics of boarding/alighting activities and its impact on bus dwell times is crucial to improving bus service levels. However, research is limited as conventional data collection methods are both time and labour intensive. In this paper, we present the first use of smart card data to study passenger boarding/alighting behaviour and its impact on bus dwell time. Given the nature of these data, we focus on passenger activity time and do not account for the time necessary to open and close doors. We study single decker, double decker and articulated buses and identify the specific effects of floor/entrance type, number of activities and occupancy on both boarding and alighting dynamics. A linear relationship between average boarding and alighting times and their respective standard deviations is also found, whereas the variability of boarding and alighting time decreases with the number of passengers boarding and alighting. After observing the cumulative boarding/alighting processes under different occupancy conditions, we propose a new model to estimate passenger activity time, by introducing critical occupancy – a parameter incorporating the friction between boarding/alighting and on-board passengers. We conduct regression analyses with the proposed and another popular model for simultaneous boarding/alighting processes, finding that the critical occupancy plays a significant role in determining the regime of boarding and alighting processes and the overall activity time. Our results provide potential implications for practice and policy, such as identifying optimal vehicle type for a particular route and modelling transit service reliability.

Suggested Citation

  • Sun, Lijun & Tirachini, Alejandro & Axhausen, Kay W. & Erath, Alexander & Lee, Der-Horng, 2014. "Models of bus boarding and alighting dynamics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 447-460.
    • Handle: RePEc:eee:transa:v:69:y:2014:i:c:p:447-460
    DOI: 10.1016/j.tra.2014.09.007
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    References listed on IDEAS

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    Cited by:

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    5. Lian, Liping & Song, Weiguo & Yuen, Kwok Kit Richard & Telesca, Luciano, 2018. "Investigating the time evolution of some parameters describing inflow processes of pedestrians in a room," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 77-88.
    6. Ji, Yanjie & Gao, Liangpeng & Chen, Dandan & Ma, Xinwei & Zhang, Ruochen, 2018. "How does a static measure influence passengers’ boarding behaviors and bus dwell time? Simulated evidence from Nanjing bus stations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 13-25.
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    9. Jiajie Yu & Yanjie Ji & Liangpeng Gao & Qi Gao, 2019. "Optimization of Metro Passenger Organizing of Alighting and Boarding Processes: Simulated Evidence from the Metro Station in Nanjing, China," Sustainability, MDPI, vol. 11(13), pages 1-20, July.
    10. You-Zhi Zeng & Bin Ran & Ning Zhang & Xiaobao Yang & Jia-Jun Shen & She-Jun Deng, 2018. "Optimal Pricing and Service for the Peak-Period Bus Commuting Inefficiency of Boarding Queuing Congestion," Sustainability, MDPI, vol. 10(10), pages 1-14, September.
    11. Liu, Xiaodong & Song, Weiguo & Fu, Libi & Fang, Zhiming, 2016. "Experimental study of pedestrian inflow in a room with a separate entrance and exit," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 224-238.
    12. Wang, Pengfei & Chen, Xuewu & Zheng, Yue & Cheng, Long & Wang, Yinhai & Lei, Da, 2021. "Providing real-time bus crowding information for passengers: A novel policy to promote high-frequency transit performance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 316-329.
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