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논문 기본 정보

자료유형
학술대회자료
저자정보
Heungseok Chae (Seoul National University) Myungsu Lee (Korea Transportation Safety Authority) Kyongsu Yi (Seoul National University)
저널정보
제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2017
발행연도
2017.10
수록면
1,640 - 1,645 (6page)

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This paper describes design and evaluation of a motion planning algorithm of automated vehicle for lane change. Autonomous lane change is necessary for highway automated driving. In a perception part, surrounding vehicles’ states are estimated and predicted. The motion of ego vehicle is also predicted and these prediction information is utilized in motion planning. In motion planning part, driving mode, which is lane keeping or lane change, target states and constraints are decided. Lane change mode decision is determined based on surrounding vehicles states and ego vehicle states. Lane change availability is decided by the safety distance that considers relative velocity and relative position of subject and surrounding vehicles. If the ego vehicle do not perform to lane change, the most proper position is selected considering the probabilistic prediction information and the safety distance. And the longitudinal control is applied to move desired merge position. A safety driving envelope is defined based on information of surrounding vehicles behaviors and is used for control constraints. In control part, the controller is designed to obtain the desired steering angle and longitudinal acceleration using a model predictive control (MPC) with constraints. The proposed automated driving algorithm has been evaluated via computer simulation studies.

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Abstract
1. INTRODUCTION
2. ARCHITECTURE OF AUTOMATED DRIVING CONTROL
3. PROBABILISTIC PREDICTION
4. Motion Planning Algorithm
5. MODEL PREDICTIVE CONTROL
6. EVALUATION RESULTS
7. CONCLUSION
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UCI(KEPA) : I410-ECN-0101-2018-003-001428357