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논문 기본 정보

자료유형
학술저널
저자정보
서은빈 (대구경북과학기술원(DGIST)) 이승기 (대구경북과학기술원(DGIST)) 여호영 (대구경북과학기술원(DGIST)) 신관준 (대구경북과학기술원(DGIST)) 최경호 (대구경북과학기술원(DGIST)) 임용섭 (대구경북과학기술원(DGIST))
저널정보
한국자동차안전학회 자동차안전학회지 자동차안전학회지 제13권 제2호
발행연도
2021.6
수록면
35 - 41 (7page)

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초록· 키워드

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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.

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ABSTRACT
1. 서론
2. Path tracking algorithm
3. Lane Detection
4. Field Test
5. 결론
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UCI(KEPA) : I410-ECN-0101-2023-556-001309110