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Project","award":["2021020TD001"],"award-info":[{"award-number":["2021020TD001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>V2P (vehicle-to-pedestrian) communication can improve road traffic efficiency, solve traffic congestion, and improve traffic safety. It is an important direction for the development of smart transportation in the future. Existing V2P communication systems are limited to the early warning of vehicles and pedestrians, and do not plan the trajectory of vehicles to achieve active collision avoidance. In order to reduce the adverse effects on vehicle comfort and economy caused by switching the \u201cstop\u2013go\u201d state, this paper uses a PF (particle filter) to preprocess GPS (Global Positioning System) data to solve the problem of poor positioning accuracy. An obstacle avoidance trajectory-planning algorithm that meets the needs of vehicle path planning is proposed, which considers the constraints of the road environment and pedestrian travel. The algorithm improves the obstacle repulsion model of the artificial potential field method, and combines it with the A* algorithm and model predictive control. At the same time, it controls the input and output based on the artificial potential field method and vehicle motion constraints, so as to obtain the planned trajectory of the vehicle\u2019s active obstacle avoidance. The test results show that the vehicle trajectory planned by the algorithm is relatively smooth, and the acceleration and steering angle change ranges are small. Based on ensuring safety, stability, and comfort in vehicle driving, this trajectory can effectively prevent collisions between vehicles and pedestrians and improve traffic efficiency.<\/jats:p>","DOI":"10.3390\/s23063248","type":"journal-article","created":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T03:30:31Z","timestamp":1679283031000},"page":"3248","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Active Obstacle Avoidance Trajectory Planning for Vehicles Based on Obstacle Potential Field and MPC in V2P Scenario"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1494-8922","authenticated-orcid":false,"given":"Ruoyu","family":"Pan","sequence":"first","affiliation":[{"name":"School of Communications and Information Engineering and School of Artificial Intelligence, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4355-3815","authenticated-orcid":false,"given":"Lihua","family":"Jie","sequence":"additional","affiliation":[{"name":"School of Communications and Information Engineering and School of Artificial Intelligence, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Communications and Information Engineering and School of Artificial Intelligence, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honggang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Communications and Information Engineering and School of Artificial Intelligence, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3682-1666","authenticated-orcid":false,"given":"Jingfeng","family":"Yang","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Industrial Intelligence, Guangzhou 511458, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiwei","family":"Song","sequence":"additional","affiliation":[{"name":"China Electronics Standardization Institute, Beijing 100007, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ma, Y., Zhu, X., Zhang, S., Yang, R., Wang, W., and Manocha, D. 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