Toward sustainable urban mobility: Investigating nonwork travel behavior in a sprawled Canadian city

ABSTRACT

The prevalence of urban sprawl, amplified levels of auto dependency, and nonwork travel during the afternoon peak hours have resulted in a steady increase in unsustainable patterns of travel in Canadian cities. Active and green modes of transportation along with smart growth have been promoted as a panacea. This article investigates the efficacy of such sustainable urban mobility strategies in Windsor, Ontario, using data records from a Household Travel Survey. Multinomial and mixed-logit models are developed to identify the factors influencing nonwork mode choice travel behavior. Next, the models are used in a scenario-building and simulation exercise to illustrate the benefits attained from jointly improving public transit, encouraging smart growth development, and lowering vehicle ownership. Based on the obtained results, embracing single-policy instruments is not an effective approach for reducing auto dependency in the study area. However, adopting a multidimensional policy approach that integrates land use and transportation policy instruments is proven more effective for achieving sustainable outcomes. It is recommended that the service and facilities for transit and nonmotorized modes be improved, and easier access to commercial and recreational activities be enhanced through progressive improvements to the built environment. Adoption of smart-growth strategies should be also pursued by planners and decision makers to create an environment conducive to reducing the levels of auto ownership. Such a goal is of paramount importance for sustainability because the level of auto ownership emerged as the most important policy instrument for reducing auto dependency in the study area.

KEYWORDS:

• Mixed logit
• nonwork trips
• simulation
• smart growth
• sprawl
• sustainable transportation

Acknowledgments

The authors thank Mr. Steve Kapusta of the City of Windsor for providing the travel survey data used herein. This research is partially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Ministry of Transportation of Ontario (MTO).