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Lightweight Map Updating for Highly Automated Driving in Non-paved Roads Hunan University
- Format:
- Book
- Conference/Event
- Author/Creator:
- Wang, Xiaowei, author.
- Conference Name:
- Automotive Technical Papers (2021-01-01 : Warrendale, Pennsylvania, United States)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2021
- Summary:
- Highly autonomous vehicles have drawn the interests of many researchers in recent years. For highly autonomous vehicles, a high-definition (HD) map is crucial since it provides accurate information for autonomous driving. However, due to the possible fast-changing environment, the performance of HD maps will deteriorate over time if timely updates are not ensured. Therefore, this paper studies the updating of lightweight HD maps in closed areas. Firstly, a novel two-layer map model called a lightweight HD map is introduced to support autonomous driving in a flexible and efficient way. Secondly, typical updating of scenarios in closed areas with non-paved roads is abstracted into operations including area border expansion, road addition, and road deletion. Meanwhile, a map updating framework is proposed to address the issue of map updating in closed areas. Finally, an experiment is conducted to demonstrate the feasibility and effectiveness of the proposed map updating approach
- Notes:
- Vendor supplied data
- Publisher Number:
- 2021-01-5032
- Access Restriction:
- Restricted for use by site license
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