Development of Obstacle Avoidance for Autonomous Vehicles and an Optimization Scheme for the Artificial Potential Field Method

The research on the driving process of autonomous vehicles involves the combination of multiple subjects including sensor perception, artificial intelligence, high-precision map, and intelligent obstacle avoidance, which is an important development direction of current road driving. To achieve the p...

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Bibliographic Details
Published in2021 2nd International Conference on Computing and Data Science (CDS) pp. 12 - 18
Main Author Yang, Xuefei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2021
Subjects
autonomous driving
Collision avoidance
Data science
development process
Histograms
Image recognition
optimization of artificial potential field method
path-planning algorithm
Roads
Robustness
Visualization
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DOI10.1109/CDS52072.2021.00010

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Summary:The research on the driving process of autonomous vehicles involves the combination of multiple subjects including sensor perception, artificial intelligence, high-precision map, and intelligent obstacle avoidance, which is an important development direction of current road driving. To achieve the purpose of autonomous driving without human control, the high adaptability and robustness of the vehicle, as well as the ability to identify and avoid obstacles while driving are required. The purpose of this paper is to study the development process of the obstacle avoidance system for autonomous vehicles and propose an optimization scheme for the obstacle avoidance algorithm.
DOI:10.1109/CDS52072.2021.00010