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Safety-Balanced Driving-Style Aware Trajectory Planning in Intersection Scenarios With Uncertain Environment | |
Wang, Xiao1,2; Tang, Ke2; Dai, Xingyuan3,4; Xu, Jintao2; Xi, Jinhao3,5; Ai, Rui2; Wang, Yuxiao3,5; Gu, Weihao2; Sun, Changyin1 | |
发表期刊 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES |
ISSN | 2379-8858 |
2023-04-01 | |
卷号 | 8期号:4页码:2888-2898 |
通讯作者 | Wang, Xiao(xiao.wang@ahu.edu.cn) |
摘要 | This paper proposes a two-stage trajectory planning method for self-driving vehicles (SDVs) in intersection scenarios with uncertain social circumstances while considering other traffic participants, which are human-driving vehicles (HDVs) with different driving styles. The mixture-of-experts approach is first utilized to learn from human-driving trajectory data to construct a multimodal motion planner, which uses a Transformer to model the interactions between vehicles by explicitly considering their driving styles to facilitate the integrated network to achieve scene-consistent multimodal trajectory prediction and candidate trajectory generation. Second, based on the generated trajectories for the SDV and the predicted trajectories for the other HDVs, each candidate planning trajectory is evaluated via a safety-balanced value function. After that, the trajectory with the highest value is selected for implementation. Such a method plans a safe and efficient driving trajectory in complex and uncertain scenarios. The experimental results demonstrate the efficiency and effectiveness of the designed method as well as the robustness and reasonableness of the SDVs' maneuver decisions at an intersection considering the behavioral dynamics of HDVs. |
关键词 | Trajectory Planning Trajectory planning Safety Predictive models Training Data models Autonomous vehicles trajectory planning social interactions uncertain circumstances |
DOI | 10.1109/TIV.2023.3239903 |
关键词[WOS] | PARALLEL INTELLIGENCE ; METAVERSES ; PREDICTION ; ASSISTANCE ; VEHICLES ; BEHAVIOR ; MODEL |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[62173329] |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Computer Science ; Engineering ; Transportation |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS记录号 | WOS:000994739000024 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/53391 |
专题 | 多模态人工智能系统全国重点实验室 |
通讯作者 | Wang, Xiao |
作者单位 | 1.Anhui Univ, Sch Artificial Intelligence, Hefei 230031, Peoples R China 2.Haomo Technol Co Ltd, Beijing 100192, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Qingdao Acad Intelligent Ind, Qingdao 266114, Peoples R China 5.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Xiao,Tang, Ke,Dai, Xingyuan,et al. Safety-Balanced Driving-Style Aware Trajectory Planning in Intersection Scenarios With Uncertain Environment[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(4):2888-2898. |
APA | Wang, Xiao.,Tang, Ke.,Dai, Xingyuan.,Xu, Jintao.,Xi, Jinhao.,...&Sun, Changyin.(2023).Safety-Balanced Driving-Style Aware Trajectory Planning in Intersection Scenarios With Uncertain Environment.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(4),2888-2898. |
MLA | Wang, Xiao,et al."Safety-Balanced Driving-Style Aware Trajectory Planning in Intersection Scenarios With Uncertain Environment".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.4(2023):2888-2898. |
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