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A Dynamic Lane-Change Trajectory Planning Algorithm Based on Minimum Safe Spacing University of Chinese Academy of Science (UCAS); Institute o.

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Li, Yao, author.
Contributor:
Li, Fang
Li, Hangeng
Tian, Fei
Wang, Lifang
Wu, Yan
Conference Name:
Automotive Technical Papers (2020-01-01 : Warrendale, Pennsylvania, United States)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2021
Summary:
As one of the key technologies in automatic driving, trajectory planning for automated lane change should not only take into account the complex and dynamic driving environment at the beginning of the lane change but also on the whole process. However, most existing researches only consider other vehicles' initial states and assume they do not change. But this may cause potential collisions because the vehicles' running states vary at all times in a real situation. One important reason that causes this problem is that the lane-change vehicle cannot acquire accurate information regarding the other vehicles. However, this situation can be effectively improved with the development of vehicle-to-vehicle communication in recent years. In this background, this paper proposes a dynamic lane-change trajectory planning algorithm based on minimum safe spacing, which can calculate a safe and comfortable trajectory for the vehicle and update it to avoid potential collisions until the lane change is complete. Therefore, it is capable of planning a reference trajectory for a normal lane change, an emergency lane change, and a change back to the original lane. Finally, we conduct simulation experiments and the results show that compared with the conventional lane-change trajectory planning algorithm, the algorithm can update the lane-change vehicle's trajectory, avoid potential collisions during the lane-change process effectively, and improve traffic efficiency on the premise of safety and comfort; compared with other dynamic lane-change trajectory planning algorithms, the algorithm can transform the complex anti-collision constraints into the objective function, which can greatly reduce the difficulty of the solution and improve the efficiency of computing
Notes:
Vendor supplied data
Publisher Number:
2020-01-5110
Access Restriction:
Restricted for use by site license

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