Evaluation of Neighbourhood Characteristics and Active Transport Mode Choice
One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1130255Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 985
 Saelens, b.e., et al., neighborhood-based differences in physical activity: an environment scale evaluation. american journal of public health, 2003. 93(9): p. 1552-1558.
 Ewing, r. And r. Cervero, travel and the built environment. Journal of the american planning association, 2010. 76(3): p. 265-294.
 M. Pratt, et al., economic interventions to promote physical activity: application of the sloth model. American journal of preventive medicine, 2004. 27(3): p. 136-145.
 Lucas, k., transport and social exclusion: where are we now? Transport policy, 2012. 20: p. 105-113.
 Altman, j. And m. Hinkson, mobility and modernity in arnhem land the social universe of kuninjku trucks. Journal of material culture, 2007. 12(2): p. 181-203.
 Johnson, v., g. Currie, and j. Stanley, exploring transport to arts and cultural activities as a facilitator of social inclusion. Transport policy, 2011. 18(1): p. 68-75.
 Handy, s.l., et al., how the built environment affects physical activity: views from urban planning. American journal of preventive medicine, 2002. 23(2): p. 64-73.
 Wang, d., y. Chai, and f. Li, built environment diversities and activity–travel behaviour variations in beijing, china. Journal of transport geography, 2011. 19(6): p. 1173-1186.
 Lee, j.-s., j. Nam, and s.-s. Lee, built environment impacts on individual mode choice: an empirical study of the houston-galveston metropolitan area. International journal of sustainable transportation, 2014. 8(6): p. 447-470.
 Boarnet, m.g., a broader context for land use and travel behavior, and a research agenda. Journal of the american planning association, 2011. 77(3): p. 197-213.
 Victorian's open data directory. Available from: https://www.data.vic.gov.au/, 15/08/ 2015
 Saghapour, t., s. Moridpour, and r.g. Thompson, estimating public transport accessibility in metropolitan areas incorporating population density, in the 95th transportation research board annual meeting. 2016, transportation research board: united states.
 Saghapour, t., s. Moridpour, and r.g. Thompson, public transport accessibility in metropolitan areas: a new approach incorporating population density. Journal of transport geography, 2016. 54: p. 273-285.
 Giles-corti, b., et al., developing a research and practice tool to measure walkability: a demonstration project. Health promotion journal of australia, 2015. 25(3): p. 160-166.
 Peiravian, f., s. Derrible, and f. Ijaz, development and application of the pedestrian environment index (pei). Journal of transport geography, 2014. 39: p. 73-84.
 Sundquist, k., et al., neighborhood walkability, physical activity, and walking behavior: the swedish neighborhood and physical activity (snap) study. Social science & medicine, 2011. 72(8): p. 1266-1273.
 Frank, l.d., et al., the development of a walkability index: application to the neighborhood quality of life study. British journal of sports medicine, 2010. 44(13): p. 924-933.
 Owen, n., et al., neighborhood walkability and the walking behavior of australian adults. American journal of preventive medicine, 2007. 33(5): p. 387-395.
 Frank, l.d., et al., many pathways from land use to health: associations between neighborhood walkability and active transportation, body mass index, and air quality. Journal of the american planning association, 2006. 72(1): p. 75-87.
 Frank, l.d., et al., linking objectively measured physical activity with objectively measured urban form: findings from smartraq. American journal of preventive medicine, 2005. 28(2): p. 117-125.
 Morse-mcnabb, e. The victorian land use information system (vluis): a new method for creating land use data for victoria, australia. In surveying and spatial sciences conference. 2011.
 Sinnott, r., et al., australian urban research infrastructure network. 2011.
 Andren, t., et al., introduction to sas. Department of economics, school of economics and commercial law, gothenburg university, 1999.
 Kim, s., s. Park, and j.s. Lee, meso-or micro-scale? Environmental factors influencing pedestrian satisfaction. Transportation research part d: transport and environment, 2014. 30: p. 10-20.
 Taniguchi, e., r.g. Thompson, and t. Yamada, concepts and visions for urban transport and logistics relating to human security. Urban transportation and logistics: health, safety, and security concerns, 2013: p. 1.
 Lamíquiz, p.j. And j. López-domínguez, 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, 2015. 74: p. 148-163.