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Developing a web-based accessibility calculator prototype for the Greater Montreal Area

Author

Listed:
  • Páez, Antonio
  • Moniruzzaman, Md.
  • Bourbonnais, Pierre-Leo
  • Morency, Catherine

Abstract

A mixture of modes is considered a key element towards sustainable transportation. New technologies that provide information about various modes and environments can help to inform choices regarding travel and accessibility. In this paper we describe the development of a web-based accessibility calculator prototype for the Greater Montreal Area in Canada. The core of this tool is a statistical model of trip length developed using the spatial expansion method. The model is used to obtain estimates of trip length for a desired profile, based on attributes such as age, gender, family structure, and mode of travel, as well as geographical location. These estimates are used to calculate a cumulative opportunities accessibility measure to different types of essential destinations. Travel behavior information is drawn from Montreal’s 2008 Household Travel Surveys. Geocoded information about trip origins and destinations is used to calculate trip length. A broad array of covariates related to individual and household attributes, and urban form are used. A geocoded business point database is used for the calculation of cumulative opportunities. To simplify the use of the accessibility calculator, the model is implemented in a user-friendly way using Google Maps API v3 and a convenient interface. Different possible uses of the accessibility calculator are illustrated in the paper. The accessibility calculator can be used by members of the public or planners/policy makers to measure the level of accessibility for a specific address and personal profile by various modes of transportation.

Suggested Citation

  • Páez, Antonio & Moniruzzaman, Md. & Bourbonnais, Pierre-Leo & Morency, Catherine, 2013. "Developing a web-based accessibility calculator prototype for the Greater Montreal Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 58(C), pages 103-115.
    • Handle: RePEc:eee:transa:v:58:y:2013:i:c:p:103-115
    DOI: 10.1016/j.tra.2013.10.020
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    Cited by:

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    3. Stewart, Anson F., 2017. "Mapping transit accessibility: Possibilities for public participation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 150-166.
    4. Xia, Nan & Cheng, Liang & Chen, Song & Wei, XiaoYan & Zong, WenWen & Li, ManChun, 2018. "Accessibility based on Gravity-Radiation model and Google Maps API: A case study in Australia," Journal of Transport Geography, Elsevier, vol. 72(C), pages 178-190.
    5. Lamíquiz, Patxi J. & López-Domínguez, Jorge, 2015. "Effects of built environment on walking at the neighbourhood scale. A new role for street networks by modelling their configurational accessibility?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 148-163.
    6. Stewart, Anson F. & Zegras, P. Christopher, 2016. "CoAXs: A Collaborative Accessibility-based Stakeholder Engagement System for communicating transport impacts," Research in Transportation Economics, Elsevier, vol. 59(C), pages 423-433.

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