Understanding short-distance travel to school in Singapore: A data-driven approach

This study examines the school travel mode of children and youth students (ages 7 to 18) in Singapore. Using a large crowdsensing dataset the paper focuses on minute-by-minute decision-making of those students living within 2.5km of school. Data-driven methods are employed in order to identify students' chosen transport mode (car, walking, taking bus or riding metro). Furthermore, we present attributes of travel mode alternatives computed by a replicable framework that utilises open sources. New algorithms are developed to identify proxies for walking access and public transport access. We found that about 19% of students in the sample live up to a distance of 2.5km from the school. From these, about 45% of trips are made by public transit (e.g., bus and metro), and only 13% are made by walking. The empirical results suggest that the public transport modes of bus and metro are not distinct. Consistent with past research based on traditional survey data, walking time and walking distance are the most influential factors in the decision to walk-to-school. Interestingly, schools' con-nectivity to the street network is found to play a key role on the shift from public transport to walking. Likewise, departing at peak hours, the odds to choose public transport modes are about 40-45% lower as compared to walk.