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Commuter cycling policy in Singapore: a farecard data analytics based approach

Author

Listed:
  • Ashwani Kumar

    (Singapore-MIT Alliance for Research and Technology (SMART))

  • Viet Anh Nguyen

    (National University of Singapore)

  • Kwong Meng Teo

    (National University of Singapore)

Abstract

Peak-hour week-day traffic congestion is a common challenge in urban mobility. Promotion of commuter cycling can help in alleviating this problem in many cities. This paper takes a data analytics approach to propose policies for promoting commuter cycling in Singapore. It uses farecard data to assess the commuter cycling potential and develops a data-driven approach to policy making. A spatio-temporal analysis of farecard data helps in finding patterns in the potential demand for first-mile as well as end-to-end cycling. This analysis is used to suggest policies like cycling towns to promote first-mile cycling and cycling regions to enable end-to-end cycling by linking together the cycling towns. Furthermore, an optimization model is developed to make efficient choice of cycling towns and links for a given budget so as to maximize the potential number of commuter cyclists.

Suggested Citation

  • Ashwani Kumar & Viet Anh Nguyen & Kwong Meng Teo, 2016. "Commuter cycling policy in Singapore: a farecard data analytics based approach," Annals of Operations Research, Springer, vol. 236(1), pages 57-73, January.
    • Handle: RePEc:spr:annopr:v:236:y:2016:i:1:d:10.1007_s10479-014-1585-7
    DOI: 10.1007/s10479-014-1585-7
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    References listed on IDEAS

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    1. Piet Rietveld, 2001. "Biking and Walking: The Position of Non-Motorised Transport Modes in Transport Systems," Tinbergen Institute Discussion Papers 01-111/3, Tinbergen Institute.
    2. Ralph Buehler & John Pucher, 2012. "Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes," Transportation, Springer, vol. 39(2), pages 409-432, March.
    3. Nankervis, Max, 1999. "The effect of weather and climate on bicycle commuting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(6), pages 417-431, August.
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    Cited by:

    1. Bram Janssens & Matthias Bogaert & Mathijs Maton, 2023. "Predicting the next Pogačar: a data analytical approach to detect young professional cycling talents," Annals of Operations Research, Springer, vol. 325(1), pages 557-588, June.
    2. Justin Longo & Alan Rodney Dobell, 2018. "The Limits of Policy Analytics: Early Examples and the Emerging Boundary of Possibilities," Politics and Governance, Cogitatio Press, vol. 6(4), pages 5-17.
    3. Che, Maohao & Wong, Yiik Diew & Lum, Kit Meng & Wang, Xueqin, 2021. "Interaction behaviour of active mobility users in shared space," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 52-65.
    4. Che, Maohao & Wong, Yiik Diew & Lum, Kit Meng & Liu, Shuai, 2024. "Impact of “keep left” measure on pedestrians, cyclists and e-scooter riders at a crossing of a signalised junction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).

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