Pedestrian crossing behavior at signalized crosswalks

Abstract

This study investigated pedestrian jaywalking at signalized crosswalks. Observational surveys were conducted at seven crosswalks in different areas in Hong Kong, after which pedestrian information and site condition data were incorporated into a database. A binary logit model was used to identify possible factors that determine the probability of pedestrian jaywalking. To address the variation in the effects of the explanatory variables among pedestrians and the unobserved heterogeneity across sites, a random parameter model and a random effect model were used, respectively. The results showed that the random parameter model performed the best in terms of goodness of fit. It was found that the signal when a pedestrian arrives at the crosswalk is critical for decision making, and the jaywalking of surrounding pedestrians also influences the pedestrian's decision to cross. The gender and walking speed of the pedestrian, vehicle flow, and site location and condition of the crosswalk were also found to significantly determine the probability of pedestrian jaywalking.