{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T10:52:32Z","timestamp":1785408752923,"version":"3.56.0"},"reference-count":23,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T00:00:00Z","timestamp":1783123200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Innovation Project of Hebei Expressway Group Co., Ltd.","award":["Y02072505KY0001"],"award-info":[{"award-number":["Y02072505KY0001"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["52472366"],"award-info":[{"award-number":["52472366"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"award":["52472366"],"award-info":[{"award-number":["52472366"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Continuous full-domain vehicle trajectories are essential for smart highway monitoring, but single-sensor roadside perception is limited by physical coverage, occlusion, and environmental sensitivity. To address continuous trajectory tracking across multiple roadside-sensing domains, this study proposes a real-time, full-domain highway trajectory tracking framework based on radar\u2013camera fusion, improved Deep-SORT, and inverse covariance intersection. At the local perception level, a two-stage object-level and decision-level fusion model is constructed, and Deep-SORT is improved using a CIoU matching strategy and an occluded target tracking controller to enhance local multi-object tracking continuity. At the cross-domain association level, a geometry-motion consistency stepwise calibration method is developed to unify adjacent sensing domains, and a CATS-ICI trajectory stitching strategy is introduced to improve trajectory association and state smoothness during sensor handover. The proposed framework was validated on a real highway test section with roadside radar, video, and drone-based ground-truth trajectories. Experimental results show that the full local method achieves an EMOTA of 92.35%, and the reconstructed full-domain trajectories achieve a successful trajectory matching rate of 98.4% under the 452 vehicles\/10 min test condition. Additional ablation experiments further verify the contributions of radar\u2013camera fusion, CIoU, OTTC, GMCSC, CATS, and ICI. These results demonstrate that the proposed framework can provide continuous and reliable full-domain vehicle trajectories for real-world highway monitoring.<\/jats:p>","DOI":"10.3390\/s26134251","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T12:01:37Z","timestamp":1783339297000},"page":"4251","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Continuous Full-Domain Highway Trajectory Tracking Based on Improved Deep-SORT and Inverse Covariance Intersection"],"prefix":"10.3390","volume":"26","author":[{"given":"Zheye","family":"Tian","sequence":"first","affiliation":[{"name":"Hebei Expressway Group Co., Ltd., Jingqin Branch, Qinhuangdao 066001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4132-0240","authenticated-orcid":false,"given":"Changhuizi","family":"Duan","sequence":"additional","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shijie","family":"Gao","sequence":"additional","affiliation":[{"name":"Hebei Expressway Group Co., Ltd., Jingqin Branch, Qinhuangdao 066001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianling","family":"Gu","sequence":"additional","affiliation":[{"name":"Hebei Expressway Group Co., Ltd., Shijiazhuang 050035, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0926-9140","authenticated-orcid":false,"given":"Nengchao","family":"Lyu","sequence":"additional","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,4]]},"reference":[{"key":"ref_1","first-page":"100986","article-title":"Smart roads: A state of the art of highways innovations in the Smart Age","volume":"25","author":"Pompigna","year":"2022","journal-title":"Eng. 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