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Summary & Details

Prediction of Road Slope Ahead of Vehicles Based on Data Fusion and Data Mining

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Format: PDF

Price: Non-members (tax incl.)：￥6,600 Members (tax incl.)：￥5,280

Paper/Info type: SAE Paper

No.2021-01-0910

Pages: 1-10(Total 10 p)

Date of publication: Apr 2021

Publisher: SAE International

Language: English

Event: SAE WCX Digital Summit 2021

Detailed Information

Author(E)	1) Meng Sun, 2) Gangfeng Tan, 3) Li Liu, 4) Zhongpeng Tian, 5) Lingtao Chen
Affiliation(E)	1) Wuhan University of Technology, 2) Suizhou-WUT Industry Research Institute, 3) Wuhan University of Technology, 4) Wuhan University of Technology, 5) Wuhan University of Technology
Abstract(E)	Heavy commercial vehicle drivers may frequently shift gears when they are running on long and downhill roads in mountainous area. In order to improve driving safety and fuel economy, it is necessary to predict the slope of the road ahead in real time and correct the driver's shift strategy in time. At present, the road slope estimation is mainly based on the real-time estimation of the road slope at the current position of the vehicle based on the vehicle driving information obtained by the sensors, but the road slope of the road section that the vehicle is about to reach has not been predicted. In this paper, based on the road slope information of the road section that the driver has driven through, combined with Geographic Information System (GIS) information and road design standards, the slope of the road section ahead is predicted. GIS information and road design standards are used to predict the overall situation of a section of road, and the slope of the first part of the section is assumed to be known. Based on these, data fusion and data mining methods are used to predict the slope of the road ahead in advance. By predicting the slope of the road ahead in advance, drivers can get advance information about the road ahead and adjust or maintain current driving strategies to improve driving safety and fuel economy.

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