Accessibility research, within the context of the social exclusion dimensions of transport, has provided valuable tools to understand the potential of people to reach daily life activity locations. In this paper, model-based estimates of distance travelled are used to calculate a cumulative opportunities measure of accessibility. Multivariate, spatially expanded models produce estimates of distance travelled that are specific to both geographical location and type of individual. Opportunity landscapes obtained based on these estimates are used for comparative accessibility analysis by means of what are termed relative accessibility deprivation indicators. The indicators proposed are demonstrated with a case study of food deserts in the city of Montreal, Canada. The results of the analysis illustrate the variations in accessibility between individuals in low-income households and the reference group, and the effect of vehicle ownership for accessibility to food services, thus highlighting the social exclusion implications of these factors.
The Toronto Area Scheduling Model for Household Agents (TASHA), a new prototype activity scheduling microsimulation model, generates activity schedules and travel patterns for a 24-h typical weekday for all persons in a household. The prototype model is based solely on conventional trip diary data and therefore is applicable in many urban areas where activity data may not be available. The model makes use of the concept of the project, a "container" of activities with a common goal, to organize activity episodes into the schedules of persons in a household. A heuristic, or rule-based, method is used to organize activities into projects and then to form schedules for interacting household members. The TASHA model is considered to be a successful first attempt to operationalize a generalized conceptual model of household decision making, with reasonable correspondence between model and observed trip rates and chain characteristics.
Three weather sensitive multinomial logit models are estimated using the 2001 Transportation Tomorrow Survey in order explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data is restricted to non-captive commuters who have the option of alternating between all five basic modes of auto driver, auto passenger, transit, bike and walk with change in weather. Daily trip rates in various weather conditions are assessed. The combined effect of the daily trip rate and mode choice analysis is applied to several climate change scenarios. A 6 o C increase in temperature can increase cycling trips by 17%, and reduce auto-passenger trips by 7%. A 20% increase or decrease in precipitation, however, is found to have much smaller impacts on all modes. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.iii
Walking to or from school may provide a regular source of physical activity for children and youth. To improve walking practices among this younger population, urban planners emphasize the importance of built environment interventions. Empirical understanding of the potential relationship between the built environment and active school transportation (e.g., walking) is therefore essential to the development of effective planning interventions. In the nexus of empiricism and policy, place-based differences in school transport policy and urbanization processes, which may associate with mode choice, provide the rationale for conducting local research to support local policy development. This study examines the association between the built environment and the likelihood of walking or being driven to or from school. The research also addresses differences in mode choice behavior across morning and afternoon school trips. Binomial logit models were specified to study the school travel outcomes of children aged 11 to 13 years in the city of Toronto, Canada. Distance between the residence and school had the strongest correlation with mode choice; other built environment measures had moderate associations with walking. Importantly, the built environment around a child's residence had a stronger association with mode choice than did the built environment around the school. Furthermore, the effect of the built environment was more apparent for home-to-school trips. This research provides evidence that the built environment may influence school travel mode choice, but planners and community-based organizations should exercise caution when the nature of interventions required to encourage walking among children is determined.
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