A heuristic model for pedestrian intention estimation

Camara, Fanta and Merat, Natasha and Fox, Charles (2019) A heuristic model for pedestrian intention estimation. In: IEEE Intelligent Transportation Systems Conference, 27th - 30th October 2019, New Zealand.

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A heuristic model for pedestrian intention estimation
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Abstract

Understanding pedestrian behaviour and controlling interactions with pedestrians is of critical importance for autonomous vehicles, but remains a complex and challenging problem. This study infers pedestrian intent during possible road-crossing interactions, to assist autonomous vehicle decisions to yield or not yield when approaching them, and tests a simple heuristic model of intent on pedestrian-vehicle trajectory data for the first time. It relies on a heuristic approach based
on the observed positions of the agents over time. The method can predict pedestrian crossing intent, crossing or stopping, with 96% accuracy by the time the pedestrian reaches the curbside, on the standard Daimler pedestrian dataset. This result is important in demarcating scenarios which have a clear winner and can be predicted easily with the simple heuristic, from those which may require more complex game-theoretic models to predict and control.

Keywords:autonomous vehicles, pedestrians, behaviour
Subjects:H Engineering > H230 Transport Engineering
Divisions:College of Science > School of Computer Science
ID Code:36758
Deposited On:22 Aug 2019 07:53

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