{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T06:13:54Z","timestamp":1783664034475,"version":"3.55.0"},"reference-count":20,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T00:00:00Z","timestamp":1725408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research Project of the Liaoning Provincial Department of Education","award":["JYTZD2023081"],"award-info":[{"award-number":["JYTZD2023081"]}]},{"name":"Key Research Project of the Liaoning Provincial Department of Education","award":["2018LNGXGJWPY-YB014"],"award-info":[{"award-number":["2018LNGXGJWPY-YB014"]}]},{"name":"Key Research Project of the Liaoning Provincial Department of Education","award":["2022-MS-376"],"award-info":[{"award-number":["2022-MS-376"]}]},{"name":"Overseas Training Program for Higher Education Institutions in Liaoning Province","award":["JYTZD2023081"],"award-info":[{"award-number":["JYTZD2023081"]}]},{"name":"Overseas Training Program for Higher Education Institutions in Liaoning Province","award":["2018LNGXGJWPY-YB014"],"award-info":[{"award-number":["2018LNGXGJWPY-YB014"]}]},{"name":"Overseas Training Program for Higher Education Institutions in Liaoning Province","award":["2022-MS-376"],"award-info":[{"award-number":["2022-MS-376"]}]},{"name":"China Liaoning Provincial Natural Fund Grant Program Project","award":["JYTZD2023081"],"award-info":[{"award-number":["JYTZD2023081"]}]},{"name":"China Liaoning Provincial Natural Fund Grant Program Project","award":["2018LNGXGJWPY-YB014"],"award-info":[{"award-number":["2018LNGXGJWPY-YB014"]}]},{"name":"China Liaoning Provincial Natural Fund Grant Program Project","award":["2022-MS-376"],"award-info":[{"award-number":["2022-MS-376"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper addresses the challenge of trajectory planning for autonomous vehicles operating in complex, constrained environments. The proposed method enhances the hybrid A-star algorithm through back-end optimization. An adaptive node expansion strategy is introduced to handle varying environmental complexities. By integrating Dijkstra\u2019s shortest path search, the method improves direction selection and refines the estimated cost function. Utilizing the characteristics of hybrid A-star path planning, a quadratic programming approach with designed constraints smooths discrete path points. This results in a smoothed trajectory that supports speed planning using S-curve profiles. Both simulation and experimental results demonstrate that the improved hybrid A-star search significantly boosts efficiency. The trajectory shows continuous and smooth transitions in heading angle and speed, leading to notable improvements in trajectory planning efficiency and overall comfort for autonomous vehicles in challenging environments.<\/jats:p>","DOI":"10.3390\/s24175746","type":"journal-article","created":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T08:46:22Z","timestamp":1725439582000},"page":"5746","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Research on Trajectory Planning of Autonomous Vehicles in Constrained Spaces"],"prefix":"10.3390","volume":"24","author":[{"given":"Yunlong","family":"Li","sequence":"first","affiliation":[{"name":"School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4501-7431","authenticated-orcid":false,"given":"Gang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xizheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3479","DOI":"10.1109\/TITS.2020.2983553","article-title":"Using Crash Databases to Predict Effectiveness of New Autonomous Vehicle Maneuvers for Lane-Departure Injury Reduction","volume":"22","author":"Olofsson","year":"2021","journal-title":"IEEE Trans. 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