This study investigates the influence of built environment factors on pedestrian route choices in an urban context using passively collected mobile phone trajectory data from Sydney, Australia. We estimate and compare multiple discrete choice models including C-Logit, Path Size Logit (PSL), and Error Component (EC) models to quantify associations between pedestrian route choices and route characteristics such as distance, slope, turns, crossings, amenities, and greenery. The models are applied to a high-resolution sidewalk network to simulate pedestrian flows across the city. Our findings are broadly consistent with existing literature, highlighting the importance of route simplicity, directness, and terrain in walking behavior. A key contribution of this study is the integration of passively collected GPS trajectories with route choice modeling and network-level flow assignment, demonstrating a scalable framework for understanding and forecasting pedestrian behavior. The approach enables city-scale assessments of pedestrian infrastructure and offers valuable insights for data-driven planning of walkable urban environments.
Lilasathapornkit et al. (Wed,) studied this question.