Recent Advances in Planning for Autonomous Driving and Mining Trucks: A Survey
Autonomous driving technology, which enhances driving safety, comfort, and reduces energy consumption, has become a prominent research focus in recent years. Path planning is a crucial component of autonomous driving technology, focusing on the optimal route for a vehicle to travel from one point to another. As a category of autonomous driving technology, the modular methods are highly favored for their interpretability and stability. However, there remains a lack of comprehensive reviews that encapsulate the most recent advancements in modular methods. Consequently, in this paper, a detailed survey of modular methods is conducted, with a particular emphasis on those pertinent to autonomous driving within the mining area. We further explore the advantages and limitations of various approaches and present commonly used vehicle models. Additionally, we provide a comprehensive overview of the current research challenges and future directions in autonomous driving technologies, with a specific focus on applications within mining area.
Authors
- Yunfeng Ai (ORCID: https://orcid.org/0000-0002-2673-1368)
- Jun Fu (ORCID: https://orcid.org/0000-0002-8723-1439)
- Meng Shi
- Xiaoyu Xiong (ORCID: https://orcid.org/0009-0003-3014-9965)
- Bin Tian (ORCID: https://orcid.org/0000-0003-1050-1282)
- Long Chen (ORCID: https://orcid.org/0000-0002-5123-5913)
Institutions
- Shandong Institute of Automation (CN)
- Beijing Academy of Artificial Intelligence (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Published
- 2024-11-01
- DOI
- https://doi.org/10.1109/cac63892.2024.10865544
- Primary Topic
- Advanced Manufacturing and Logistics Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Hebei Province
- National Key Research and Development Program of China