Embodied Intelligence-Based Perception, Decision-Making, and Control for Autonomous Operations of Rail Transportation
This perspective proposes a framework for autonomous operations of rail transportation based on embodied intelligence to enhance environmental adaptation and autonomous decision-making capabilities. Three key technologies are outlined to enable perception, decision-making, and control in rail transportation, i.e., embodied perception for active environmental understanding, embodied execution, and embodied learning and evolution. It also explores the main challenges of implementing embodied intelligence-based autonomous operations. The proposed framework offers new insights and directions for practitioners in the rail transportation industry.
Authors
- Haifeng Song (ORCID: https://orcid.org/0000-0001-9840-5804)
- Min Zhou (ORCID: https://orcid.org/0000-0002-9286-1726)
- Wen‐Hua Chen (ORCID: https://orcid.org/0000-0003-3356-2889)
- Hongwei Wang (ORCID: https://orcid.org/0000-0001-5713-3988)
- Hairong Dong (ORCID: https://orcid.org/0000-0003-4369-3401)
- Nan Zheng (ORCID: https://orcid.org/0000-0002-8560-9231)
Institutions
- Loughborough University (GB)
- Chinese Academy of Sciences (CN)
- Beijing Jiaotong University (CN)
- Institute of Automation (CN)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Vehicles
- Published
- 2024-12-16
- DOI
- https://doi.org/10.1109/tiv.2024.3517335
- Citations
- 14
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 9.01
Funders
- National Natural Science Foundation of China