Hazard-based duration approach for understanding pedestrian crossing risk exposure at signalised intersection crosswalks – A case study of Kolkata, India

Abstract

Pedestrian signal violation is a significant concern among policymakers and traffic engineers as this leads to a pedestrian-vehicle crash. The waiting time for a pedestrian at intersections is crucial in street-crossing decision-making. Once pedestrians terminate their waiting behaviour during the red-light period, they would cross in the red light and put themselves in danger. A total of 2089 red-light arriving pedestrian observations were made at eight intersection crosswalks across Kolkata city (India). With the help of hazard-based duration models, the waiting duration till signal violation has been analysed. Kaplan–Meier curve has been plotted to understand the survival probabilities. A semi-parametric Cox Proportional Hazard model was used to understand the different factors influencing signal violation behaviour. However, the proportional hazard assumption was not satisfied. Therefore, a parametric Accelerated Failure Time (AFT) model was used to understand the various covariates that affect the waiting duration. The results highlighted that 49.5% of pedestrians crossed immediately after arriving at the intersection in the red-light phase. A pedestrian’s probability of crossing the road when it is unsafe, i.e., motor vehicles still have green or yellow, varies with the waiting time. As waiting time increases, pedestrians get impatient and violate the traffic signal. This violation places them at an increased risk of being struck by a motor vehicle. The covariate analysis using the AFT model showed that pedestrian glance/looking behaviour, different types of distractions, signal cycle length, carrying luggage, and traffic plying on the road impacted signal violation behaviour. Signal modifications by reducing red-light phase length for pedestrians might be the most efficient means of reducing the likelihood of signal violation and being hit by a motor vehicle.