Walkable Neighbourhoods: Empirical Analysis of Factors Influencing Pedestrian Behaviour

In pedestrian travel behaviour modelling, the variable that represents the number of walking trips must be carefully considered when there is a high number of zero values. This study employs Zero-inflated Poisson regression to account for these excess zeros when analysing the frequency of walking trips. Using data from the 2013 Greater Mumbai region activity travel diary survey, census data, and an accessibility index (walk score), the paper estimates Poisson models at the individual level for the frequency of walking trips for commuting and non-commuting purposes on a single travel day. The results indicate that pedestrian socio-demographics (such as age, workplace schedule, public transportation usage, type of residence, and household income) and characteristics of the built environment (such as population density and accessibility index) have an impact on walking behaviour for both commuting and non-commuting purposes. These pedestrian travel behaviour models can be used for evaluating public health and sustainability policy and planning.