This paper examines the relationships between the built environment—both ‘neighborhood’ design characteristics and relative location—and motor vehicle ownership and use in a rapidly motorising, developing city context, that of Santiago de Chile. A vehicle choice model suggests that income dominates the household vehicle ownership decision, but also detects a relationship between several built environment characteristics and a household’s likelihood of car ownership. A second model, directly linked to the ownership model to correct for selection bias and endogeneity, suggests a strong relationship with locational characteristics like distance to the central business district and Metro stations. Elasticities of vehicle kilometres travelled (VKT), calculated via the combined models, suggest that income plays the overall largest single role in determining VKT. In combination, however, a range of different design and relative location characteristics also display a relatively strong association with VKT.
Abstract:The Future Mobility Survey (FMS) is a smartphone-based prompted-recall travel survey that aims to support data collection initiatives for transport modeling purposes. This paper details the considerations that have gone into its development, including the smartphone apps for iPhone and Android platforms, the online activity diary and user interface, and the background intelligence for processing collected data into activity locations and travel traces. We discuss the various trade-offs regarding user comprehension, resource use, and participant burden, including findings from usability tests and a pilot study. We find that close attention should be paid to the simplicity of the user interaction, determinations of activity locations (such as the false positive/false negative trade-off in their automatic classification), and the clarity of interactions in the activity diary. The FMS system design and implementation provides pragmatic, useful insights into the development of similar platforms and approaches for travel/activity surveys.
Urban mobility significantly contributes to global carbon dioxide emissions. Given the rapid expansion and growth in urban areas, cities thus require innovative policies to ensure efficient and sustainable mobility. Urban typologies can serve as a vehicle for understanding dynamics of cities, which exhibit high variability in form, economic output, mobility behavior, among others. Yet, typologies relevant for sustainable urban mobility analyses are few, outdated and not large enough in scope. In this paper, we present a new typologization spanning 331 cities in 124 countries. Our sample represents 40% of the global urban population and contains the most recent data from 2008 to date. Using a factor analytic and agglomerative clustering approach, we identify 9 urban factors and 12 typologies. We discuss the implications of this new framework for researchers and planners and investigate the relationships between mobility and environmental sustainability indicators. Notably, we show an immediate application of the urban typologies to better understanding travel behavior and also describe their usage for detailed large-scale simulation in representative prototype cities for insights into sustainable future mobility policy pathways. Our data and results are publicly available for further exploration and will serve as a foundation for future analyses toward desirable urban and environmental outcomes.
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