[논문]실시간 이미지 처리 방법을 이용한 개선된 차선 인식 경로 추종 알고리즘 개발

서은빈; 이승기; 여호영; 신관준; 최경호; 임용섭

doi:10.22680/kasa2021.13.2.035

[국내논문] 실시간 이미지 처리 방법을 이용한 개선된 차선 인식 경로 추종 알고리즘 개발
Development of an Improved Geometric Path Tracking Algorithm with Real Time Image Processing Methods 원문보기

자동차안전학회지 = Journal of Auto-Vehicle Safety Association, v.13 no.2, 2021년, pp.35 - 41

서은빈 (대구경북과학기술원(DGIST) 융복합대학) , 이승기 (대구경북과학기술원(DGIST) 융복합대학) , 여호영 (대구경북과학기술원(DGIST) 융복합대학) , 신관준 (대구경북과학기술원(DGIST) 융복합대학) , 최경호 (대구경북과학기술원(DGIST) 융합전공) , 임용섭 (대구경북과학기술원(DGIST) 로봇공학전공)

Abstract ▼ AI-Helper

In this study, improved path tracking control algorithm based on pure pursuit algorithm is newly proposed by using improved lane detection algorithm through real time post-processing with interpolation methodology. Since the original pure pursuit works well only at speeds below 20 km/h, the look-ahead distance is implemented as a sigmoid function to work well at an average speed of 45 km/h to improve tracking performance. In addition, a smoothing filter was added to reduce the steering angle vibration of the original algorithm, and the stability of the steering angle was improved. The post-processing algorithm presented has implemented more robust lane recognition system using real-time pre/post processing method with deep learning and estimated interpolation. Real time processing is more cost-effective than the method using lots of computing resources and building abundant datasets for improving the performance of deep learning networks. Therefore, this paper also presents improved lane detection performance by using the final results with naive computer vision codes and pre/post processing. Firstly, the pre-processing was newly designed for real-time processing and robust recognition performance of augmentation. Secondly, the post-processing was designed to detect lanes by receiving the segmentation results based on the estimated interpolation in consideration of the properties of the continuous lanes. Consequently, experimental results by utilizing driving guidance line information from processing parts show that the improved lane detection algorithm is effective to minimize the lateral offset error in the diverse maneuvering roads.

Keyword

표/그림 (9)

그림 Fig. 1 Pure Pursuit Geometry
그림 Fig. 2 Comparison of images after the shadow augmentation and images on a sunny day
그림 Fig. 3 Example of segmentation image
표 Table 1 Test Course Detail
그림 Fig. 4 The result images with and without shadow augmentation respectively
그림 Fig. 5 Comparison of the images without the lane detection algorithm and images with algorithm
그림 Fig. 6 Actual driving path according to the presence of filters added to pure pursuit
표 Table 2 Look-ahead Distance Comparison
그림 Fig. 7 Steer graph according to the presence of filters added to pure pursuit

참고문헌 (9)

Park, M., Lee, S., and Han, W., 2014, "Development of lateral control system for autonomous vehicle based on adaptive pure pursuit algorithm", 2014 14th International Conference on Control, Automation and Systems (ICCAS 2014), Seoul, pp. 1443~1447.
Wallace, R. S., Stentz, A., Thorpe, C. E., Moravec, H. P., Whittaker, W., and Kanade, T., 1985, "First Results in Robot Road-Following", International Joint Conference on Artificial Intelligence (IJCAI), pp. 1089~1095.
Hoffmann, G. M., Tomlin, C. J., Montemerlo, M., and Thrun, S., 2007, "Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing", 2007 American Control Conference, pp. 2296~2301.
Wit, J., Crane III, C. D., and Armstrong, D., 2004, "Autonomous ground vehicle path tracking", Journal of Robotic Systems, Vol. 21, No. 8, pp. 439~449.

상세보기
Martinez, J. L., Morales, J., Mandow, A., and Garcia-Cerezo, A., 2008, "Steering limitations for a vehicle pulling passive trailers", IEEE Transactions on Control Systems Technology, Vol. 16, No. 4, pp. 809~818.

상세보기
Wang, W. J., Hsu, T. M., and Wu, T. S., 2017, "The improved pure pursuit algorithm for autonomous driving advanced system", 2017 IEEE 10th International Workshop on Computational Intelligence and Applications (IWCIA), pp. 33~38.
Wang, R., Li, Y., Fan, J., Wang, T., and Chen, X. 2020, "A Novel Pure Pursuit Algorithm for Autonomous Vehicles Based on Salp Swarm Algorithm and Velocity Controller", IEEE Access, 8, pp. 166525~166540.

상세보기
Hou, Y., Ma, Z., Liu, C., and Loy, C. C., 2019, "Learning lightweight lane detection cnns by self attention distillation", In Proceedings of the IEEE International Conference on Computer Vision, pp. 1013~1021.
Gasca, M., and Sauer, T., 2000, "Polynomial interpolation in several variables", Advances in Computational Mathematics, Vol. 12, No. 4, p. 377.

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증