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Effect of integration of bicyclists and pedestrians with transit in New Delhi

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  • Mohanty, Sudatta
  • Bansal, Sugam
  • Bairwa, Khushi

Abstract

Traditionally, transportation mode shares in cities have been calculated separately for walking, bicycling and transit. However, it is well known that all transit trips have an access and egress component which is mostly executed through walking or bicycling. Hence, the choice of whether to choose transit for a particular trip depends as much on the walking or bicycling component of the trip as the transit component itself. A major source of inaccuracy in traditional mode share estimation models is the failure to identify this inherent dependence of transit trips on bicycling and walking. In New Delhi, where almost all access and egress trips for buses are made by bicycle/walking, the inaccuracies in mode share estimation could be more significant. This research aims to study behavioral effects of integrating bicycling and walking infrastructure with transit and provide predictions for outcomes of policy implementations modifying bicycle-to-transit or walk-to-transit environment in New Delhi. Four policy variables each are selected that affect pedestrian access to transit (sidewalk width, lighting, crossings and surrounding hygiene) and bicycle access to transit (bicycle lane, bicycle parking, bicycle sharing and on-board vehicle capacity) respectively. To gauge user behavior for hypothetical situations, stated preference survey data is collected through intercept surveys. 90 respondents were interviewed with upto 10 choice scenarios per individual with a total of 897 scenario responses (461 Pedestrian Infrastructure Scenarios +436 Bicycle Infrastructure Scenarios). Choice modelling is performed through a simple Multinomial Logit (MNL) model (in case there is no significant heterogeneity among individual preferences) and Random-Taste Mixed Logit model (to incorporate significant heterogeneity among various types of individual preferences). Modelling results showed that among pedestrian infrastructure, only presence of crossings could affect transit use and there is possibly significant heterogeneity in the population regarding use of sidewalks. Among bicycle infrastructure variables, presence of bicycle lanes and bicycle sharing is expected to positively impact transit use with no significant heterogeneity among the population. Finally, based on modelling results, three policy implementation scenarios are tested – presence of pedestrian crossings near all transit stops, introduction of bicycle lanes throughout the city and introduction of bicycle sharing system throughout the city. The scenario analysis shows possibility of considerable rise in transit mode share and GHG emission savings. This motivates further research to corroborate these findings with a larger sample, evaluation of viability of the ideas and possibly investigating implementation details.

Suggested Citation

  • Mohanty, Sudatta & Bansal, Sugam & Bairwa, Khushi, 2017. "Effect of integration of bicyclists and pedestrians with transit in New Delhi," Transport Policy, Elsevier, vol. 57(C), pages 31-40.
    • Handle: RePEc:eee:trapol:v:57:y:2017:i:c:p:31-40
    DOI: 10.1016/j.tranpol.2017.03.019
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    References listed on IDEAS

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    1. Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
    2. Bhat, Chandra R., 1998. "Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(7), pages 495-507, September.
    3. Givoni, Moshe & Rietveld, Piet, 2007. "The access journey to the railway station and its role in passengers' satisfaction with rail travel," Transport Policy, Elsevier, vol. 14(5), pages 357-365, September.
    4. Bunch, David S. & Bradley, Mark & Golob, Thomas F. & Kitamura, Ryuichi & Occhiuzzo, Gareth P., 1993. "Demand for clean-fuel vehicles in California: A discrete-choice stated preference pilot project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(3), pages 237-253, May.
    5. Rose, John M. & Bliemer, Michiel C.J. & Hensher, David A. & Collins, Andrew T., 2008. "Designing efficient stated choice experiments in the presence of reference alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 395-406, May.
    6. Brons, Martijn & Givoni, Moshe & Rietveld, Piet, 2009. "Access to railway stations and its potential in increasing rail use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(2), pages 136-149, February.
    7. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    8. Ben-Akiva, M. & Bolduc, D. & Bradley, M., 1993. "Estimation of Travel Choice Models with Randomly Distributed Values of Time," Papers 9303, Laval - Recherche en Energie.
    9. Geetam Tiwari, 2011. "Key Mobility Challenges in Indian Cities," International Transport Forum Discussion Papers 2011/18, OECD Publishing.
    10. Martens, Karel, 2007. "Promoting bike-and-ride: The Dutch experience," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(4), pages 326-338, May.
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