{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T17:19:53Z","timestamp":1778347193009,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T00:00:00Z","timestamp":1686960000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2022YFD2001405"],"award-info":[{"award-number":["2022YFD2001405"]}]},{"name":"National Key Research and Development Program of China","award":["CARS-28-20"],"award-info":[{"award-number":["CARS-28-20"]}]},{"name":"National Key Research and Development Program of China","award":["20181112"],"award-info":[{"award-number":["20181112"]}]},{"name":"National Modern Agricultural Industrial Technology System of China","award":["2022YFD2001405"],"award-info":[{"award-number":["2022YFD2001405"]}]},{"name":"National Modern Agricultural Industrial Technology System of China","award":["CARS-28-20"],"award-info":[{"award-number":["CARS-28-20"]}]},{"name":"National Modern Agricultural Industrial Technology System of China","award":["20181112"],"award-info":[{"award-number":["20181112"]}]},{"name":"2115 Talent Development Program of China Agricultural University and Foundation for State Key Laboratory of Automotive Simulation and Control","award":["2022YFD2001405"],"award-info":[{"award-number":["2022YFD2001405"]}]},{"name":"2115 Talent Development Program of China Agricultural University and Foundation for State Key Laboratory of Automotive Simulation and Control","award":["CARS-28-20"],"award-info":[{"award-number":["CARS-28-20"]}]},{"name":"2115 Talent Development Program of China Agricultural University and Foundation for State Key Laboratory of Automotive Simulation and Control","award":["20181112"],"award-info":[{"award-number":["20181112"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The stable detection and tracking of high-speed vehicles on the road by using LiDAR can input accurate information for the decision-making module and improve the driving safety of smart cars. This paper proposed a novel LiDAR-based robust vehicle detection method including three parts: point cloud clustering, bounding box fitting and point cloud recognition. Firstly, aiming at the problem of clustering quality degradation caused by the uneven distribution of LiDAR point clouds and the difference in clustering radius between point cloud clusters in traditional DBSCAN (TDBSCAN) obstacle clustering algorithms, an improved DBSCAN algorithm based on distance-adaptive clustering radius (ADBSCAN) is designed, and a point cloud KD-Tree data structure is constructed to speed up the traversal of the algorithm; meanwhile, the OPTICS algorithm is introduced to enhance the performance of the proposed algorithm. Then, by adopting different fitting strategies for vehicle contour points in various states, the adaptability of the bounding box fitting algorithm is improved; Moreover, in view of the shortcomings of the poor robustness of the L-shape algorithm, the principal component analysis method (PCA) is introduced to obtain stable bounding box fitting results. Finally, considering the time-consuming and low-accuracy training of traditional machine learning algorithms, advanced PointNet in deep learning technique is built to send the point cloud within the bounding box of a high-confidence vehicle into PointNet to complete vehicle recognition. Experiments based on our autonomous driving perception platform and the KITTI dataset prove that the proposed method can stably complete vehicle target recognition and achieve a good balance between time-consuming and accuracy.<\/jats:p>","DOI":"10.3390\/rs15123160","type":"journal-article","created":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T01:59:51Z","timestamp":1687139991000},"page":"3160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Robust LiDAR-Based Vehicle Detection for On-Road Autonomous Driving"],"prefix":"10.3390","volume":"15","author":[{"given":"Xianjian","family":"Jin","sequence":"first","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China"},{"name":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0652-8933","authenticated-orcid":false,"given":"Xiongkui","family":"He","sequence":"additional","affiliation":[{"name":"College of Agricultural Unmanned System, China Agricultural University, Beijing 100193, China"},{"name":"College of Science, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guohua","family":"Liu","sequence":"additional","affiliation":[{"name":"Shanghai Tenghao Vision Technology Limited Company, Shanghai 201107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zeyuan","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qikang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhan, J., Duan, C., Guan, X., Lu, P., and Yang, K. 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