{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T19:27:29Z","timestamp":1776454049624,"version":"3.51.2"},"reference-count":22,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Innovation Fund Project of Industry, University and Research of Chinese Universities","award":["2024HT007"],"award-info":[{"award-number":["2024HT007"]}]},{"name":"Innovation Fund Project of Industry, University and Research of Chinese Universities","award":["JYTZD2023081"],"award-info":[{"award-number":["JYTZD2023081"]}]},{"name":"Innovation Fund Project of Industry, University and Research of Chinese Universities","award":["2018LNGXGJWPY-YB014"],"award-info":[{"award-number":["2018LNGXGJWPY-YB014"]}]},{"name":"Key Research Project of Liaoning Provincial Department of Education","award":["2024HT007"],"award-info":[{"award-number":["2024HT007"]}]},{"name":"Key Research Project of Liaoning Provincial Department of Education","award":["JYTZD2023081"],"award-info":[{"award-number":["JYTZD2023081"]}]},{"name":"Key Research Project of Liaoning Provincial Department of Education","award":["2018LNGXGJWPY-YB014"],"award-info":[{"award-number":["2018LNGXGJWPY-YB014"]}]},{"name":"Overseas Cultivation Project for Higher Education Institutions in Liaoning Province","award":["2024HT007"],"award-info":[{"award-number":["2024HT007"]}]},{"name":"Overseas Cultivation Project for Higher Education Institutions in Liaoning Province","award":["JYTZD2023081"],"award-info":[{"award-number":["JYTZD2023081"]}]},{"name":"Overseas Cultivation Project for Higher Education Institutions in Liaoning Province","award":["2018LNGXGJWPY-YB014"],"award-info":[{"award-number":["2018LNGXGJWPY-YB014"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>For the local oscillation phenomenon of the APF algorithm in the face of static U-shaped obstacles, the path cusp phenomenon caused by the vehicle corner and path curvature constraints is not taken into account, as well as the low path safety caused by ignoring the vehicle volume constraints. Therefore, an APF-Dijkstra path planning fusion algorithm based on steering model and volume constraints is proposed to improve it. First, perform an expansion treatment on the obstacles in the map, optimize the search direction of the Dijkstra algorithm and its planned global path, ensuring that the distance between the path and the expanded grid is no less than 1 m, and use the path points as temporary target points for the APF algorithm. Secondly, a Gaussian function is introduced to optimize the potential energy function of the APF algorithm, and the U-shaped obstacle is ellipticized, and a virtual target point is used to provide the gravitational force. Again, the three-point arc method based on the steering model is used to determine the location of the predicted points and to smooth the paths in real time while constraining the steering angle. Finally, a 4.5 m \u00d7 2.5 m vehicle rectangle is used instead of the traditional mass points to make the algorithm volumetrically constrained. Meanwhile, a model for detecting vehicle collisions is established to cover the rectangle boundary with 14 envelope circles, and the combined force of the computed mass points is transformed into the combined force of the computed envelope circles to further improve path safety. The algorithm is validated by simulation experiments, and the results show that the fusion algorithm can avoid static U-shaped obstacles and dynamic obstacles well; the curvature change rate of the obstacle avoidance path is 0.248, 0.162, and 0.169, and the curvature standard deviation is 0.16, which verifies the smoothness of the fusion algorithm. Meanwhile, the distances between the obstacles and the center of the rear axle of the vehicle are all higher than 1.60 m, which verifies the safety of the fusion algorithm.<\/jats:p>","DOI":"10.3390\/a18070403","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T04:04:22Z","timestamp":1751342662000},"page":"403","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Research on APF-Dijkstra Path Planning Fusion Algorithm Based on Steering Model and Volume Constraints"],"prefix":"10.3390","volume":"18","author":[{"given":"Xizheng","family":"Wang","sequence":"first","affiliation":[{"name":"School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"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":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijian","family":"Bian","sequence":"additional","affiliation":[{"name":"School of Automobile and Traffic Engineering, Liaoning University of Technology, Jinzhou 121001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"012060","DOI":"10.1088\/1742-6596\/2033\/1\/012060","article-title":"Research on UAV path planning obstacle avoidance algorithm based on improved artificial potential field method","volume":"1948","author":"Qi","year":"2021","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wang, X., Li, G., and Bian, Z. (2025). Research on the A* Algorithm Based on Adaptive Weights and Heuristic Reward Values. World Electr. Veh. J., 16.","DOI":"10.3390\/wevj16030144"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, J., Liu, B., Guo, D., Gao, X., and Wang, P. (2024). An improved RRT path-planning algorithm based on vehicle lane-change trajectory data. World Electr. Veh. J., 15.","DOI":"10.3390\/wevj15110481"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Li, L., Jiang, L., Tu, W., Jiang, L., and He, R. (2024). Smooth and efficient path planning for car-like mobile robot using improved ant colony optimization in narrow and large-size scenes. Fractal Fract., 8.","DOI":"10.3390\/fractalfract8030157"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Wang, Z., and Li, G. (2024). 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[6th ed.]."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/18\/7\/403\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:02:00Z","timestamp":1760032920000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/18\/7\/403"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,1]]},"references-count":22,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["a18070403"],"URL":"https:\/\/doi.org\/10.3390\/a18070403","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,1]]}}}