An End-to-End autonomous driving model based on visual perception for temporary roads
The experimental results demonstrate that our End-to-End model accurately identifies temporary roads. The trajectory planning time for a single frame is approximately 100 ms, while the average trajectory deviation is 0.689 m. This performance meets the real-time processing requirements for low-speed vehicles, enabling unmanned vehicles to execute tracking tasks in temporary road environments.
Authors
- Min Xie
- Liyong Wang (ORCID: https://orcid.org/0000-0002-0527-7063)
- Qinghua Su (ORCID: https://orcid.org/0009-0007-6145-6326)
- Yue Song (ORCID: https://orcid.org/0000-0003-1573-5643)
- Ao Cui
- Zhengqiu Xie (ORCID: https://orcid.org/0000-0003-2593-2288)
Institutions
- Beijing Information Science & Technology University (CN)
Publication Details
- Journal
- PeerJ Computer Science
- Published
- 2025-08-29
- DOI
- https://doi.org/10.7717/peerj-cs.3152
- Primary Topic
- Autonomous Vehicle Technology and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China