Autonomous Driving in Unstructured Off‐Road Environments: How Far Have We Come?

ABSTRACT Research on autonomous driving in unstructured outdoor environments is less advanced than in structured urban settings due to challenges like environmental diversities and scene complexity. These environments–such as rural areas and rugged terrains–pose unique obstacles that are not common in structured urban areas. Despite these difficulties, autonomous driving in unstructured outdoor environments is crucial for applications in agriculture, mining, and military operations. Our survey reviews over 250 papers for autonomous driving in unstructured outdoor environments, covering offline mapping, pose estimation, environmental perception, path planning, end‐to‐end autonomous driving, datasets, and relevant challenges. We also discuss emerging trends and future research directions. This review aims to consolidate knowledge and encourage further research for autonomous driving in unstructured environments. To support ongoing work, we maintain an active repository of up‐to‐date literature and open‐source projects at: https://github.com/chaytonmin/Survey‐Autonomous‐Driving‐in‐Unstructured‐Environments .

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Publication Details

Journal
Journal of Field Robotics
Published
2026-03-08
DOI
https://doi.org/10.1002/rob.70154
Primary Topic
Robotics and Sensor-Based Localization
Type
article
Field-Weighted Citation Impact
0.00
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article

Autonomous Driving in Unstructured Off‐Road Environments: How Far Have We Come?

Shubin Si, Hanzhang Xue, Erke Shang, Jilin Mei et al.
Journal of Field Robotics
Robotics and Sensor-Based Localization
article

Autonomous Driving in Unstructured Off‐Road Environments: How Far Have We Come?

Shubin Si, Hanzhang Xue, Erke Shang, Jilin Mei, Mengmeng Li, Chen Min, Liang Xiao, Xu Wang, Weizhong Jiang, Dawei Zhao, Bin Dai, Hao Fu, Yiming Nie, Qi Zhu, Yu Hu, Zitong Chen, Zhipeng Xiao
article en

Abstract

ABSTRACT Research on autonomous driving in unstructured outdoor environments is less advanced than in structured urban settings due to challenges like environmental diversities and scene complexity. These environments–such as rural areas and rugged terrains–pose unique obstacles that are not common in structured urban areas. Despite these difficulties, autonomous driving in unstructured outdoor environments is crucial for applications in agriculture, mining, and military operations. Our survey reviews over 250 papers for autonomous driving in unstructured outdoor environments, covering offline mapping, pose estimation, environmental perception, path planning, end‐to‐end autonomous driving, datasets, and relevant challenges. We also discuss emerging trends and future research directions. This review aims to consolidate knowledge and encourage further research for autonomous driving in unstructured environments. To support ongoing work, we maintain an active repository of up‐to‐date literature and open‐source projects at: https://github.com/chaytonmin/Survey‐Autonomous‐Driving‐in‐Unstructured‐Environments .

Journal of Field Robotics
Harbin University (CN), National University of Defense Technology (CN), Institute of Computing Technology (CN), Defense Systems (United States) (US), Wuhu Hit Robot Technology Research Institute (CN), Beihang University (CN)
Sustainable cities and communities
Openalex Percentile: Top 30%
Robotics and Sensor-Based Localization
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