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Evaluating the impacts of a new transit system on commuting mode choice using a GEV model estimated to revealed preference data: A case study of the VIVA system in York Region, Ontario

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  • Forsey, David
  • Habib, Khandker Nurul
  • Miller, Eric J.
  • Shalaby, Amer

Abstract

The Regional Municipality of York, north of the City of Toronto, introduced a new bus service known as VIVA in 2005. This distinctly branded system operates primarily in two highly-travelled corridors and features high operating speeds, offline fare payment, advanced traveller information systems, and other ITS technologies. Although this new service has been deemed a success by many, it remains to be seen to what degree local work and post-secondary school transit use was affected by its introduction. To evaluate this, home-based work and post-secondary school trip mode choice models are estimated by using the datasets collected after the opening of the service. These models are then used to evaluate the impacts of the system on commuting mode choice preferences by using an additional dataset collected before opening the service. A GEV model is used to capture heterogeneity reflected in the RP datasets. The paper shows how modelling can be used to assess how level of service variables (e.g. travel times) can explain the impacts of new transit service. Empirical models reveal that the introduction of VIVA impacted the mode choice preference structure in the study area for work and post-secondary school trips. Also, it is shown that the improvements in transit service had greater impacts on transit mode share than the impacts of increasing traffic congestion. It is also posited that VIVA attributes such as improved branding, advertising, and communications may have caused this change in preferences.

Suggested Citation

  • Forsey, David & Habib, Khandker Nurul & Miller, Eric J. & Shalaby, Amer, 2013. "Evaluating the impacts of a new transit system on commuting mode choice using a GEV model estimated to revealed preference data: A case study of the VIVA system in York Region, Ontario," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 1-14.
    • Handle: RePEc:eee:transa:v:50:y:2013:i:c:p:1-14
    DOI: 10.1016/j.tra.2013.01.033
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    3. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
    4. Creemers, Lieve & Tormans, Hans & Bellemans, Tom & Janssens, Davy & Wets, Geert & Cools, Mario, 2015. "Knowledge of the concept Light Rail Transit: Exploring its relevance and identification of the determinants of various knowledge levels," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 31-43.
    5. Chakrabarti, Sandip, 2022. "Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts," Transport Policy, Elsevier, vol. 115(C), pages 251-261.

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