Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance
With the development of intelligent vehicles and autonomous driving technology, the safety of vulnerable road user (VRU) in traffic has been more guaranteed, and many research achievements have been made in the key area of collision avoidance decision-making methods. In this paper, the knowledge map...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Maximum Academic Press
2023-02-01
|
| Series: | Digital Transportation and Safety |
| Subjects: | |
| Online Access: | https://www.maxapress.com/article/doi/10.48130/DTS-2023-0003 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850199860479787008 |
|---|---|
| author | Quan Yuan Yiwei Gao Jiangqi Zhu Hui Xiong Qing Xu Jianqiang Wang |
| author_facet | Quan Yuan Yiwei Gao Jiangqi Zhu Hui Xiong Qing Xu Jianqiang Wang |
| author_sort | Quan Yuan |
| collection | DOAJ |
| description | With the development of intelligent vehicles and autonomous driving technology, the safety of vulnerable road user (VRU) in traffic has been more guaranteed, and many research achievements have been made in the key area of collision avoidance decision-making methods. In this paper, the knowledge mapping method is used to mine the available literature in depth, and it is found that the research focus has shifted from the traditional accident cause analysis to emerging deep learning and virtual reality technology. This paper summarizes research on the three core dimensions of environmental perception, behavior cognition and collision avoidance decision-making in intelligent vehicle systems. In terms of perception, accurate identification of pedestrians and cyclists in complex environments is a major demand for VRU perception; in terms of behavior cognition, the coupling of VRU intention identification and motion trajectory prediction and other multiple factors needs further research; in terms of decision-making, the intention identification and trajectory prediction of collision objects are not included in the risk assessment model, and there is a lack of exploration specifically for cyclists' collision risk. On this basis, this paper provides guidance for the improvement of traffic safety of contemporary VRU under the conditions of intelligent and connected transportation. |
| format | Article |
| id | doaj-art-eba37e68d63545e9afe4ec4ce3522c67 |
| institution | OA Journals |
| issn | 2837-7842 |
| language | English |
| publishDate | 2023-02-01 |
| publisher | Maximum Academic Press |
| record_format | Article |
| series | Digital Transportation and Safety |
| spelling | doaj-art-eba37e68d63545e9afe4ec4ce3522c672025-08-20T02:12:30ZengMaximum Academic PressDigital Transportation and Safety2837-78422023-02-0121233510.48130/DTS-2023-0003DTS-2023-0003Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidanceQuan Yuan0Yiwei Gao1Jiangqi Zhu2Hui Xiong3Qing Xu4Jianqiang Wang5State Key Laboratory of Automotive Safety and Energy, School of Vehicle & Mobility, Tsinghua University, Beijing 100084, ChinaChina University of Political Science and Law, Beijing 100192, ChinaChina University of Political Science and Law, Beijing 100192, ChinaState Key Laboratory of Automotive Safety and Energy, School of Vehicle & Mobility, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Automotive Safety and Energy, School of Vehicle & Mobility, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Automotive Safety and Energy, School of Vehicle & Mobility, Tsinghua University, Beijing 100084, ChinaWith the development of intelligent vehicles and autonomous driving technology, the safety of vulnerable road user (VRU) in traffic has been more guaranteed, and many research achievements have been made in the key area of collision avoidance decision-making methods. In this paper, the knowledge mapping method is used to mine the available literature in depth, and it is found that the research focus has shifted from the traditional accident cause analysis to emerging deep learning and virtual reality technology. This paper summarizes research on the three core dimensions of environmental perception, behavior cognition and collision avoidance decision-making in intelligent vehicle systems. In terms of perception, accurate identification of pedestrians and cyclists in complex environments is a major demand for VRU perception; in terms of behavior cognition, the coupling of VRU intention identification and motion trajectory prediction and other multiple factors needs further research; in terms of decision-making, the intention identification and trajectory prediction of collision objects are not included in the risk assessment model, and there is a lack of exploration specifically for cyclists' collision risk. On this basis, this paper provides guidance for the improvement of traffic safety of contemporary VRU under the conditions of intelligent and connected transportation.https://www.maxapress.com/article/doi/10.48130/DTS-2023-0003vulnerable road usersperceptionbehavioral cognitioncollision avoidance decision-makingknowledge mapping |
| spellingShingle | Quan Yuan Yiwei Gao Jiangqi Zhu Hui Xiong Qing Xu Jianqiang Wang Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance Digital Transportation and Safety vulnerable road users perception behavioral cognition collision avoidance decision-making knowledge mapping |
| title | Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance |
| title_full | Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance |
| title_fullStr | Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance |
| title_full_unstemmed | Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance |
| title_short | Summarizing vehicle driving decision-making methods on vulnerable road user collision avoidance |
| title_sort | summarizing vehicle driving decision making methods on vulnerable road user collision avoidance |
| topic | vulnerable road users perception behavioral cognition collision avoidance decision-making knowledge mapping |
| url | https://www.maxapress.com/article/doi/10.48130/DTS-2023-0003 |
| work_keys_str_mv | AT quanyuan summarizingvehicledrivingdecisionmakingmethodsonvulnerableroadusercollisionavoidance AT yiweigao summarizingvehicledrivingdecisionmakingmethodsonvulnerableroadusercollisionavoidance AT jiangqizhu summarizingvehicledrivingdecisionmakingmethodsonvulnerableroadusercollisionavoidance AT huixiong summarizingvehicledrivingdecisionmakingmethodsonvulnerableroadusercollisionavoidance AT qingxu summarizingvehicledrivingdecisionmakingmethodsonvulnerableroadusercollisionavoidance AT jianqiangwang summarizingvehicledrivingdecisionmakingmethodsonvulnerableroadusercollisionavoidance |