Natural Vision Based Method for Predicting Pedestrian Behaviour in Urban Environments

Abstract : This paper proposes to model pedestrian behaviour in urban scenes by combining the principles of urban planning and the sociological concept of Natural Vision. This model assumes that the environment perceived by pedestrians is composed of multiple potential fields that influence their behaviour. These fields are derived from static scene elements like side-walks, cross-walks, buildings, shops entrances and dynamic obstacles like cars and buses for instance. Using this model, autonomous cars increase their level of situational awareness in the local urban space, with the ability to infer probable pedestrian paths in the scene to predict, for example, legal and illegal crossings.
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Communication dans un congrès
IEEE 20th International Conference on Intelligent Transportation Systems, Oct 2017, Yokohama, Japan
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https://hal.inria.fr/hal-01561029
Contributeur : Pavan Vasishta <>
Soumis le : mardi 25 juillet 2017 - 14:32:41
Dernière modification le : mardi 24 octobre 2017 - 10:20:01

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  • HAL Id : hal-01561029, version 1

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Pavan Vasishta, Dominique Vaufreydaz, Anne Spalanzani. Natural Vision Based Method for Predicting Pedestrian Behaviour in Urban Environments. IEEE 20th International Conference on Intelligent Transportation Systems, Oct 2017, Yokohama, Japan. 〈hal-01561029〉

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