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Driver Intent Prediction and Collision Avoidance With Barrier Functions
Yousaf Rahman; Abhishek Sharma; Mrdjan Jankovic; Mario Santillo; Michael Hafner
Source PublicationIEEE/CAA Journal of Automatica Sinica
ISSN2329-9266
2023
Volume10Issue:2Pages:365-375
AbstractFor autonomous vehicles and driver assist systems, path planning and collision avoidance algorithms benefit from accurate predictions of future location of other vehicles and intent of their drivers. In the literature, the algorithms that provide driver intent belong to two categories: those that use physics based models with some type of filtering, and machine learning based approaches. In this paper we employ barrier functions (BF) to decide driver intent. BFs are typically used to prove safety by establishing forward invariance of an admissible set. Here, we decide if the “target” vehicle is violating one or more possibly fictitious (i.e., non-physical) barrier constraints determined based on the context provided by the road geometry. The algorithm has a very small computational footprint and better false positive and negative rates than some of the alternatives. The predicted intent is then used by a control barrier function (CBF) based collision avoidance system to prevent unnecessary interventions, for either an autonomous or human-driven vehicle.
DOI10.1109/JAS.2023.123210
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50851
Collection学术期刊_IEEE/CAA Journal of Automatica Sinica
Recommended Citation
GB/T 7714
Yousaf Rahman,Abhishek Sharma,Mrdjan Jankovic,et al. Driver Intent Prediction and Collision Avoidance With Barrier Functions[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(2):365-375.
APA Yousaf Rahman,Abhishek Sharma,Mrdjan Jankovic,Mario Santillo,&Michael Hafner.(2023).Driver Intent Prediction and Collision Avoidance With Barrier Functions.IEEE/CAA Journal of Automatica Sinica,10(2),365-375.
MLA Yousaf Rahman,et al."Driver Intent Prediction and Collision Avoidance With Barrier Functions".IEEE/CAA Journal of Automatica Sinica 10.2(2023):365-375.
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