Estimating Driver Behaviour at Unsignalized Crosswalks

This research investigates driver-yielding behaviour at unsignalized crosswalks, focusing on pedestrian characteristics, and oncoming vehicle factors. The study uses data from two-lane, two-way divided roads, and drone video footage to capture vehicle trajectories and pedestrian behaviour at the median or further lanes. Driver-yielding rates are accurately captured using TRACKER 5.0 software, and the behavior is modelled using binary logistic regression. The study found that yielding patterns are similar across different vehicle categories, but factors influencing drivers’ willingness include the number of female pedestrians, the number of pedestrians in the median, the number of injured pedestrians, and the vehicle position/vehicle approaching the lane. The research contributes to understanding and addressing the complexities of unsignalized pedestrian crossings, laying the groundwork for future traffic management strategies to create safer, more efficient urban environments for pedestrians and drivers.