{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T15:38:07Z","timestamp":1774712287534,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T00:00:00Z","timestamp":1695859200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Safe-D University Transportation Center and the Center for International Intelligent Transportation Research","award":["CIITR 185923-00015"],"award-info":[{"award-number":["CIITR 185923-00015"]}]},{"name":"Safe-D University Transportation Center and the Center for International Intelligent Transportation Research","award":["JJKH20221020K"],"award-info":[{"award-number":["JJKH20221020K"]}]},{"name":"Safe-D University Transportation Center and the Center for International Intelligent Transportation Research","award":["2022-389"],"award-info":[{"award-number":["2022-389"]}]},{"name":"Scientific Research Project of the Education Department of Jilin Province","award":["CIITR 185923-00015"],"award-info":[{"award-number":["CIITR 185923-00015"]}]},{"name":"Scientific Research Project of the Education Department of Jilin Province","award":["JJKH20221020K"],"award-info":[{"award-number":["JJKH20221020K"]}]},{"name":"Scientific Research Project of the Education Department of Jilin Province","award":["2022-389"],"award-info":[{"award-number":["2022-389"]}]},{"name":"Qingdao Social Science Planning Research Project","award":["CIITR 185923-00015"],"award-info":[{"award-number":["CIITR 185923-00015"]}]},{"name":"Qingdao Social Science Planning Research Project","award":["JJKH20221020K"],"award-info":[{"award-number":["JJKH20221020K"]}]},{"name":"Qingdao Social Science Planning Research Project","award":["2022-389"],"award-info":[{"award-number":["2022-389"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>By the end of the 2020s, full autonomy in autonomous driving may become commercially viable in certain regions. However, achieving Level 5 autonomy requires crucial collaborations between vehicles and infrastructure, necessitating high-speed data processing and low-latency capabilities. This paper introduces a vehicle tracking algorithm based on roadside LiDAR (light detection and ranging) infrastructure to reduce the latency to 100 ms without compromising the detection accuracy. We first develop a vehicle detection architecture based on ResNet18 that can more effectively detect vehicles at a full frame rate by improving the BEV mapping and the loss function of the optimizer. Then, we propose a new three-stage vehicle tracking algorithm. This algorithm enhances the Hungarian algorithm to better match objects detected in consecutive frames, while time\u2013space logicality and trajectory similarity are proposed to address the short-term occlusion problem. Finally, the system is tested on static scenes in the KITTI dataset and the MATLAB\/Simulink simulation dataset. The results show that the proposed framework outperforms other methods, with F1-scores of 96.97% and 98.58% for vehicle detection for the KITTI and MATLAB\/Simulink datasets, respectively. For vehicle tracking, the MOTA are 88.12% and 90.56%, and the ID-F1 are 95.16% and 96.43%, which are better optimized than the traditional Hungarian algorithm. In particular, it has a significant improvement in calculation speed, which is important for real-time transportation applications.<\/jats:p>","DOI":"10.3390\/s23198143","type":"journal-article","created":{"date-parts":[[2023,9,28]],"date-time":"2023-09-28T07:50:26Z","timestamp":1695887426000},"page":"8143","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Vehicle Detection and Tracking with Roadside LiDAR Using Improved ResNet18 and the Hungarian Algorithm"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9098-2666","authenticated-orcid":false,"given":"Ciyun","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Traffic Information and Control Engineering, Jilin University No. 5988, Renmin Street, Changchun 130022, China"},{"name":"Jilin Engineering Research Center for Intelligent Transportation System, Changchun 130022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2289-9718","authenticated-orcid":false,"given":"Ganghao","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Traffic Information and Control Engineering, Jilin University No. 5988, Renmin Street, Changchun 130022, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5438-5565","authenticated-orcid":false,"given":"Dayong","family":"Wu","sequence":"additional","affiliation":[{"name":"Texas A&M Transportation Institute, 12700 Park Central Dr., Suite 1000, Dallas, TX 75251, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9765-1763","authenticated-orcid":false,"given":"Chen","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Traffic Information and Control Engineering, Jilin University No. 5988, Renmin Street, Changchun 130022, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,28]]},"reference":[{"key":"ref_1","unstructured":"Litman, T. 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