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At first, a safe collision distance model is established in the upper path planning layer, utilizing a vehicle point mass model and based on the distance relationship between the vehicle and obstacles. The design of the planning layer improves the safety of the vehicle. After solving the optimization problem, the optimal input variable is derived and then transmitted to the dynamic control layer for accurate tracking. It is followed by designing the triggered condition according to the stability and feasibility of the system, which reduces the computation of the controller and improves the real-time performance of the system. Finally, the simulation results demonstrate the efficacy of the proposed control strategy in addressing the obstacle avoidance challenge faced by autonomous vehicles in complex road conditions. Compared with traditional model predictive control (MPC), this strategy improves the precision of tracking control and reduces the computational complexity.<\/jats:p>","DOI":"10.1177\/01423312251334432","type":"journal-article","created":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T05:39:51Z","timestamp":1748237991000},"page":"2128-2140","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Event-triggered model predictive control for autonomous vehicle active obstacle avoidance"],"prefix":"10.1177","volume":"48","author":[{"given":"Wenjie","family":"Wu","sequence":"first","affiliation":[{"name":"College of Electrical and Information Engineering, Lanzhou University of Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9563-9074","authenticated-orcid":false,"given":"Zhiwen","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Lanzhou University of Technology, China"},{"name":"Gansu Key Laboratory Advanced Control for Industrial Processes, Lanzhou University of Technology, China"},{"name":"National Experimental Teaching Center of Electrical and Control Engineering, Lanzhou University of Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7666-3114","authenticated-orcid":false,"given":"Jindou","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Lanzhou University of Technology, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Miao","sequence":"additional","affiliation":[{"name":"Gansu-Unis Intelligent Transportation System and control Technology Co., Ltd, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"issue":"2","key":"e_1_3_2_2_1","first-page":"2239","article-title":"Trajectory tracking of autonomous vehicle based on model predictive control with PID feedback","volume":"24","author":"Chu D","year":"2022","unstructured":"Chu D, Li H, Zhao C, et al. 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