Towards full autonomous driving: challenges and frontiers
With the rapid advancement of information technology and intelligent systems, autonomous driving has garnered significant attention and research in recent years. Key technologies, such as Simultaneous Localization and Mapping (SLAM), Perception and Localization, and Scene Segmentation, have proven to be essential in this field. These technologies not only evolve independently, each with its own research focus and application paths, but also complement and rely on one another in various complex autonomous driving scenarios. This paper provides a comprehensive review of the development and current state of these technologies, along with a forecast of their future trends.
Authors
- Wenxin Chen (ORCID: https://orcid.org/0000-0003-4263-2826)
- Wei He (ORCID: https://orcid.org/0000-0002-8944-9861)
- Shiqiang Tian
- Lingfeng Zhang
Institutions
- Shanghai Jiao Tong University (CN)
- Fudan University (CN)
- Jiangsu University of Technology (CN)
Publication Details
- Journal
- Frontiers in Physics
- Published
- 2024-10-18
- DOI
- https://doi.org/10.3389/fphy.2024.1485026
- Citations
- 4
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 5.20
Funders
- National Natural Science Foundation of China
- Changzhou Science and Technology Bureau
- Jiangsu Provincial Department of Education