적응형 순항제어 상황에서의 위험도 기반 차선 변경 최적제어 알고리즘에 대한 연구

Study on TTC-based optimal lane change algorithm in adaptive cruise control
Citations

SCOPUS

4

초록

The advanced driver assistance system for autonomous vehicles is being researched and developed for driving stability and driver convenience. Autonomous driving systems, such as adaptive cruise control(ACC), lane keeping assistance(LKA), and lane change system(LCS), have been developed, and they are being applied to many vehicles. The most important goal of these advanced control systems is to improve safety. In this paper, we propose an optimal lane change controller while considering the crash risk by using the information of the preceding vehicle and the side lane vehicle for a safe lane change. The optimal controller for the lane change is designed by using the vehicle state space model. Furthermore, the time-to-collision(TTC), which is a risk index, is applied to the optimal controller. We compared the simulation result of the TTC-based optimal controller with that of the optimal controller by using a constant weighting factor. The optimal controller was developed in Matlab/Simulink, and the vehicle dynamics simulator, CarSim, was used for controller verification and comparison of results.

키워드

Adaptive cruise controlAdvanced driver assistance systemAutonomous vehicleLane change controlLane keeping assistanceOptimal controlTime-to-collisionVehicle dynamics
제목
적응형 순항제어 상황에서의 위험도 기반 차선 변경 최적제어 알고리즘에 대한 연구
제목 (타언어)
Study on TTC-based optimal lane change algorithm in adaptive cruise control
저자
나원빈김진욱이형철
DOI
10.7467/KSAE.2019.27.8.627
발행일
2019-08
유형
Article
저널명
한국자동차공학회 논문집
27
8
페이지
627 ~ 636

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