arXiv AI By Logine M. Zaki, Catherine M. Elias

INTENT: An LSTM Framework for Vehicle Intention Prediction in Intersection Scenarios with Comprehensive Ablation Analysis

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arXiv:2607. 08316v1 Announce Type: new Abstract: Vehicle intention prediction is a pivotal aspect in the agility and safety of autonomous vehicles in all driving scenarios; if genuine enhancement of autonomous vehicles are required, we need to make them adopt human interpretation of driver's intention especially in cases that require a lot of human interaction as well as complex driving behaviors like the ones at intersections, roundabouts and emergency cases such as sudden stops where vehicle intention prediction helps in taking the correct evasive action within a real time period where every second of action makes an impact and can prevent a catastrophe from taking place.

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arXiv Machine Learning
Sep 25

Safety-oriented pedestrian trajectory prediction at urban intersections using time-to-collision and crossing-zone context

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By Erel Avineri, Yftach Gil, Yehudit Aperstein