Assessment pedestrian crossing safety using vehicle-pedestrian interaction data through two different approaches

Fixed videography (FV) vs In-Motion Videography (IMV)

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Abstract

A significant portion of pedestrian accidents occurs in the outskirts areas due to the high vehicle speed and lack of safety facilities for pedestrians. Behavioral study on drivers and pedestrians is the key to better understand the causes of pedestrian accidents in order to develop safety models. Despite numerous studies on pedestrian safety based on various roads, outskirt areas have not been considered. Hence, the present study focuses on evaluating the safety of pedestrian crossing in urban and outskirt areas and to determine the differences of drivers and pedestrians’ behaviors between these areas through data based on fixed videography (FV) and in-motion videography (IMV). These approaches may lead to an exact analysis of the behavioral differences of road users behaviors from the perspective of pedestrians (FV data) and drivers (IMV data) in urban and outskirts roads. Accordingly, behavioral studies were conducted at urban and outskirts sites through FV as well as IMV using the behavior of 29 participants in the same roads in Babol city, Iran. The gap acceptance model using linear regression and pedestrian crossing probability model using logistic regression for both approaches showed similarity on results in both urban and outskirts roads. Furthermore, behaviors of pedestrians crossing and drivers’ yielding on urban and outskirts roads were very similar. Vehicle speed, the distance of vehicle to pedestrian at the possible collision point, size of pedestrian groups, and waiting time before crossing were the most important behavioral differences of pedestrian for choosing a gap acceptance and probability of crossing on various sites through two different approaches. The inference of the models obtained in this study will lead to a better understanding of the behavior of road users for studies on advanced driving assistance systems (ADAS).

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