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A Study of Low-Friction Road Estimation usinganArtificial Neural-Network Hyundai Motor Company
- Format:
- Conference/Event
- Author/Creator:
- Seo, Seo, author.
- Conference Name:
- WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)
- Language:
- English
- Physical Description:
- 1 online resource
- Place of Publication:
- Warrendale, PA SAE International 2018
- Summary:
- Road friction estimation algorithms had been studied for many years because it is very important factor for safety control and fuel efficiency of vehicle. But traditional solutions are hard to adapt in automotive industry because their performance is not sufficient enough and expensive to implement. Therefore, this paper proposes a road friction estimation algorithm based on a trained artificial neural-network which is low cost and robust. The suggested method doesn't need expensive additional sensors such as optical or lidar sensor, also it shows better performance in real car environment compared to other algorithms based on vehicle dynamics. In this paper, we would describe this algorithm in detail and analyze the test results evaluated in real road conditions
- Notes:
- Vendor supplied data
- Publisher Number:
- 2018-01-0811
- Access Restriction:
- Restricted for use by site license
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