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http://dx.doi.org/10.22680/kasa2022.14.2.014

V2V based Cut-In Vehicle Yield Algorithm for Congested Traffic Autonomous Driving  

Kim, Changhee (서울대학교 기계항공공학부)
Chae, Heungseok (서울대학교 기계항공공학부)
Yoon, Youngmin (서울대학교 기계항공공학부)
Yi, Kyongsu (서울대학교 기계항공공학부)
Publication Information
Journal of Auto-vehicle Safety Association / v.14, no.2, 2022 , pp. 14-19 More about this Journal
Abstract
This paper presents motion planning algorithm that yields to intervening side lane vehicles in a congested traffic flow based on vehicle to vehicle (V2V) communication. Autonomous driving in dense traffic situation requires advanced driving performance in terms of vehicle interaction and risk mitigation. One of the most important functions necessary for congested traffic autonomous driving is to predict the lane change intention of the side lane target vehicle. However, implementing this function by using only environmental sensors has limitations. In this study, V2V communication is used to overcome the limitations and determine the intention of cut-in vehicles. Lane change intention of the intervening side lane vehicle is inferred by its longitudinal speed, steering angle, and turn signal light information received by the on-board-unit (OBU). Once the yield decision is made, the subject vehicle decelerates to generate sufficient clearance for the target vehicle to enter. Validation of the algorithm was conducted with actual autonomous test vehicles.
Keywords
Autonomous driving; Congested traffic; Motion planning; Vehicle-to-Vehicle communication (V2V);
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