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.

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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

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article

Embodied Intelligence-Based Perception, Decision-Making, and Control for Autonomous Operations of Rail Transportation

Haifeng Song, Min Zhou, Wen‐Hua Chen, Hongwei Wang et al.
14 citations
IEEE Transactions on Intelligent Vehicles
Human-Automation Interaction and Safety
9.01
article

Embodied Intelligence-Based Perception, Decision-Making, and Control for Autonomous Operations of Rail Transportation

Haifeng Song, Min Zhou, Wen‐Hua Chen, Hongwei Wang, Hairong Dong, Nan Zheng
article en
14 citations

Abstract

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.

IEEE Transactions on Intelligent VehiclesVol. 10(12)
Loughborough University (GB), Chinese Academy of Sciences (CN), Beijing Jiaotong University (CN), Institute of Automation (CN), Beihang University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Human-Automation Interaction and Safety
9.01
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Embodied Intelligence-Based Perception, Decision-Making, and Control for Autonomous Operations of Rail Transportation — Haifeng Song, Min Zhou, et al. · IEEE Transactions on Intelligent Vehicles (2024) | TGRS Research Map | TGRS