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- W1976741595 abstract "Pedestrian protection is an important issue for intelligent vehicles. This paper proposes a new approach for predicting the possibility of a collision between a vehicle and a pedestrian. Almost all pedestrian behavior toward vehicles observed in the real world is considered safe. Therefore, pedestrian behavior that deviates from usual pedestrian behavior indicates a possibility where the vehicle must take urgent evasive action to avoid collision with the pedestrian. From such a viewpoint, this paper proposes a method for predicting whether the pedestrian behavior deviates from usual pedestrian behavior. Usual pedestrian behavior as observed from the vehicle is modeled with machine learning to detect whether a new observed behavior deviates from the model of the usual pedestrian behavior. The effectiveness of the proposed method is demonstrated with an experiment conducted in a simple road environment." @default.
- W1976741595 created "2016-06-24" @default.
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- W1976741595 date "2010-06-01" @default.
- W1976741595 modified "2023-09-27" @default.
- W1976741595 title "Detecting unusual pedestrian behavior toward own vehicle for vehicle-to-pedestrian collision avoidance" @default.
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- W1976741595 doi "https://doi.org/10.1109/ivs.2010.5548050" @default.
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