Author
Listed:
- Wenchen Yang
(National Engineering Laboratory for Surface Transportation Weather Impacts Prevention, Broadvision Engineering Consultants Co., Ltd., Kunming 650200, China
Yunnan Key Laboratory of Digital Communications, Kunming 650103, China
Key Laboratory of Transportation Meteorology, China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210008, China)
- Bijiang Tian
(National Engineering Laboratory for Surface Transportation Weather Impacts Prevention, Broadvision Engineering Consultants Co., Ltd., Kunming 650200, China
Yunnan Key Laboratory of Digital Communications, Kunming 650103, China)
- Yuwei Fang
(National Engineering Laboratory for Surface Transportation Weather Impacts Prevention, Broadvision Engineering Consultants Co., Ltd., Kunming 650200, China
Yunnan Key Laboratory of Digital Communications, Kunming 650103, China)
- Difei Wu
(Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China)
- Linyi Zhou
(Key Laboratory of Transportation Meteorology, China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210008, China)
- Juewei Cai
(Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, Shanghai 201804, China)
Abstract
Hydroplaning risk evaluation plays a pivotal role in highway safety management. It is also an important component in the intelligent transportation system (ITS) ensuring human driving safety. Water-film is the widely accepted vital factor resulting in hydroplaning and thus continuously gained researchers’ attention in recent years. This paper provides a new framework to evaluate the hydroplaning potential based on emerging 3D laser scanning technology and water-film thickness estimation. The 3D information of the road surface was captured using a vehicle-mounted Light Detection and Ranging (LiDAR) system and then processed by a wavelet-based filter to remove the redundant information (surrounding environment: trees, buildings, and vehicles). Then, the water film thickness on the given road surface was estimated based on a proposed numerical algorithm developed by the two-dimensional depth-averaged Shallow Water Equations (2DDA-SWE). The effect of the road surface geometry was also investigated based on several field test data in Shanghai, China, in January 2021. The results indicated that the water-film is more likely to appear on the rutting tracks and the pavement with local unevenness. Based on the estimated water-film, the hydroplaning speeds were then estimated to represent the hydroplaning risk of asphalt pavement in rainy weather. The proposed method provides new insights into the water-film estimation, which can help drivers make effective decisions to maintain safe driving.
Suggested Citation
Wenchen Yang & Bijiang Tian & Yuwei Fang & Difei Wu & Linyi Zhou & Juewei Cai, 2022.
"Evaluation of Highway Hydroplaning Risk Based on 3D Laser Scanning and Water-Film Thickness Estimation,"
IJERPH, MDPI, vol. 19(13), pages 1-18, June.
Handle:
RePEc:gam:jijerp:v:19:y:2022:i:13:p:7699-:d:845993
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