Pedestrian Attribute Analysis Using Agent-Based Modeling

Abstract

Crossing a road outside of a crosswalk is a major cause of pedestrian fatalities. The aim of this study was to investigate this type of behavior for different pedestrian attributes in terms of risk and gap acceptance using agent-based modeling techniques. An agent-based model was developed and tested to represent pedestrian behavior in different situations. Different pedestrian attributes were analyzed, including gender, age, type of clothing, carrying bags, using mobile phones, and crossing in a group. The results showed that pedestrians add a positive risk factor to the speed of approaching vehicles before evaluating a gap, then proceed with the crossing decision. The factor for the female pedestrians was smaller in comparison to their male counterparts, which may infer that they are more prone to taking risks during crossing compared to male pedestrians. Another interpretation can be that they have a better ability to discern vehicle speeds and thus a better assessment of the critical gap. Compared to pedestrians crossing individually, the factor was smaller for pedestrians crossing in a group, which can be an indication that pedestrians have a higher sense of safety when crossing as a group. Moreover, the analysis suggested that there is no difference in perception between old and middle-age pedestrians, pedestrians carrying bags or not, and pedestrians using a mobile phone while crossing or not. These results can be useful in evaluating pedestrian safety at midblock crossings and providing a framework for modeling this type of behavior in simulation models.