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http://dx.doi.org/10.22680/kasa2019.11.3.037

Longitudinal Motion Planning of Autonomous Vehicle for Pedestrian Collision Avoidance  

Kim, Yujin (서울대학교 차량 동역학 및 제어 연구실)
Moon, Jongsik (서울대학교 차량 동역학 및 제어 연구실)
Jeong, Yonghwan (서울대학교 차량 동역학 및 제어 연구실)
Yi, Kyongsu (서울대학교 차량 동역학 및 제어 연구실)
Publication Information
Journal of Auto-vehicle Safety Association / v.11, no.3, 2019 , pp. 37-42 More about this Journal
Abstract
This paper presents an autonomous acceleration planning algorithm for pedestrian collision avoidance at urban. Various scenarios between pedestrians and a vehicle are designed to maneuver the planning algorithm. To simulate the scenarios, we analyze pedestrian's behavior and identify limitations of fusion sensors, lidar and vision camera. Acceleration is optimally determined by considering TTC (Time To Collision) and pedestrian's intention. Pedestrian's crossing intention is estimated for quick control decision to minimize full-braking situation, based on their velocity and position change. Feasibility of the proposed algorithm is verified by simulations using Carsim and Simulink, and comparisons with actual driving data.
Keywords
Autonomous Vehicle; Active Safety; Collision Avoidance; Pedestrian; Acceleration control;
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  • Reference
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