Understanding Pedestrian Behavior in Complex Traffic Scenes

Designing autonomous vehicles for urban environments remains an unresolved problem. One major dilemma faced by autonomous cars is understanding the intention of other road users and communicating with them. To investigate one aspect of this, specifically pedestrian crossing behavior, the authors have collected a large dataset of pedestrian samples at crosswalks under various conditions (e.g., weather) and in different types of roads. Using the data, the authors analyzed pedestrian behavior from two different perspectives: the way they communicate with drivers prior to crossing and the factors that influence their behavior. The authors' study shows that changes in head orientation in the form of looking or glancing at the traffic is a strong indicator of crossing intention. The authors also found that context in the form of the properties of a crosswalk (e.g., its width), traffic dynamics (e.g., speed of the vehicles) as well as pedestrian demographics can alter pedestrian behavior after the initial intention of crossing has been displayed. The authors' findings suggest that the contextual elements can be interrelated, meaning that the presence of one factor may increase/decrease the influence of other factors. Overall, the authors' work formulates the problem of pedestrian-driver interaction and sheds light on its complexity in typical traffic scenarios.


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  • Accession Number: 01666354
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Mar 22 2018 3:16PM