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Understanding Pedestrian Behavior in Complex Traffic Scenes
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DOI：10.1109/TIV.2017.2788193.png)
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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, we 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, we analyzed pedestrian behavior from two different perspectives: the way they communicate with drivers prior to crossing and the factors that influence their behavior. Our study shows that changes in head orientation in the form of looking or glancing at the traffic is a strong indicator of crossing intention. We 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. Our 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, our work formulates the problem of pedestrian-driver interaction and sheds light on its complexity in typical traffic scenarios.
Keyword:
Autonomous driving
intelligent vehicles
driver-pedestrian interaction
human intention and behavior analysis
pedestrian behavior understanding
safety and collision avoidance
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Pedestrian-driver communication and decision strategies at marked crossings在标记的十字路口进行行人与驾驶员的沟通和决策策略
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