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Inicio  /  Applied Sciences  /  Vol: 14 Par: 4 (2024)  /  Artículo
ARTÍCULO
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Motion Planning for Autonomous Vehicles in Unanticipated Obstacle Scenarios at Intersections Based on Artificial Potential Field

Rui Mu    
Wenhao Yu    
Zhongxing Li    
Changjun Wang    
Guangming Zhao    
Wenhui Zhou and Mingyue Ma    

Resumen

This work designed a motion planning algorithm for autonomous vehicles in unanticipated obstacle scenarios. In standard driving scenarios, the proposed motion planning algorithm plans a trajectory that complies with intersection regulations, including lane-marking, recommended turning lane, traffic light, right-of-way, and no-parking rules. In unanticipated obstacle scenarios, after the necessity of obstacle avoidance is identified, the ego vehicle would break the rules temporarily to ensure the safety and mobility of autonomous vehicles.

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