Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation

Understanding the sideslip risks of various trajectory patterns, as well as the impact of rainfall on them, is critical for improving road safety. However, the lack of precise classification indicators hampers systematic analysis of the variations in vehicle trajectory patterns. To address this, thi...

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Main Authors: Wang, Bo, Wong, Yiik Diew, Zhang, Chi, Zhang, Hong, Gao, Yanyang
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/178289
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1782892024-06-14T15:33:38Z Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation Wang, Bo Wong, Yiik Diew Zhang, Chi Zhang, Hong Gao, Yanyang School of Civil and Environmental Engineering Engineering Road safety Vehicle stability Understanding the sideslip risks of various trajectory patterns, as well as the impact of rainfall on them, is critical for improving road safety. However, the lack of precise classification indicators hampers systematic analysis of the variations in vehicle trajectory patterns. To address this, this study proposes a parameterized classification method for trajectories on curved segments, employing the radius and offset of the trajectory as the primary classification features and dividing the trajectories into nine patterns. These patterns represent variations from smaller to larger radii and inside to outside lane offsets, reflecting different driving behaviors and vehicle stability during vehicle cornering. Concurrently, the friction coefficient utilization rate is used to effectively compare vehicles' sideslip risk under different weather conditions. Based on this, we construct a framework using computer vision technology for automatically identifying trajectory patterns and measuring sideslip risk. We conducted an empirical study on a highway-curved segment with high sideslip risk in China and collected two datasets under clear and rainy conditions for analysis. The classification results show that the proposed method can effectively classify trajectories according to nine trajectory patterns. Comparative analysis reveals that vehicle trajectories in both the inside and outside lanes are notably more affected by rainfall compared to the middle lane. Meanwhile, trucks demonstrate a higher susceptibility to rainfall than cars. In addition, the analysis of the sideslip risk for different trajectory patterns discovers several high-risk patterns. This study provides an effective approach for monitoring and analyzing the sideslip risk on curved segments, thereby contributing to the enhancement of road design and traffic safety management. Published version A fair amount of the research works is conducted at the Nanyang Technological University Singapore to which the first author was attached as a visiting PhD candidate sponsored by the China Scholarship Council. This work was supported by the Key Technologies Research and Development Program of China (Grant No. 2020YFC1512005), the Key Research and Development Program of Sichuan Province (Grant No. 2022YFG0048), the Key Research and Development Program of Shanxi Province (Grant No.202102020101014), and the Science and Technology Project of Sichuan Transportation Department (Grant Nos. 2019-ZL-12 and 2022-ZL-04). 2024-06-11T00:49:17Z 2024-06-11T00:49:17Z 2024 Journal Article Wang, B., Wong, Y. D., Zhang, C., Zhang, H. & Gao, Y. (2024). Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation. Journal of Advanced Transportation, 2024, 1-19. https://dx.doi.org/10.1155/2024/3138719 0197-6729 https://hdl.handle.net/10356/178289 10.1155/2024/3138719 2-s2.0-85184842648 2024 1 19 en Journal of Advanced Transportation © 2024 Bo Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Road safety
Vehicle stability
spellingShingle Engineering
Road safety
Vehicle stability
Wang, Bo
Wong, Yiik Diew
Zhang, Chi
Zhang, Hong
Gao, Yanyang
Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
description Understanding the sideslip risks of various trajectory patterns, as well as the impact of rainfall on them, is critical for improving road safety. However, the lack of precise classification indicators hampers systematic analysis of the variations in vehicle trajectory patterns. To address this, this study proposes a parameterized classification method for trajectories on curved segments, employing the radius and offset of the trajectory as the primary classification features and dividing the trajectories into nine patterns. These patterns represent variations from smaller to larger radii and inside to outside lane offsets, reflecting different driving behaviors and vehicle stability during vehicle cornering. Concurrently, the friction coefficient utilization rate is used to effectively compare vehicles' sideslip risk under different weather conditions. Based on this, we construct a framework using computer vision technology for automatically identifying trajectory patterns and measuring sideslip risk. We conducted an empirical study on a highway-curved segment with high sideslip risk in China and collected two datasets under clear and rainy conditions for analysis. The classification results show that the proposed method can effectively classify trajectories according to nine trajectory patterns. Comparative analysis reveals that vehicle trajectories in both the inside and outside lanes are notably more affected by rainfall compared to the middle lane. Meanwhile, trucks demonstrate a higher susceptibility to rainfall than cars. In addition, the analysis of the sideslip risk for different trajectory patterns discovers several high-risk patterns. This study provides an effective approach for monitoring and analyzing the sideslip risk on curved segments, thereby contributing to the enhancement of road design and traffic safety management.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
Wang, Bo
Wong, Yiik Diew
Zhang, Chi
Zhang, Hong
Gao, Yanyang
format Article
author Wang, Bo
Wong, Yiik Diew
Zhang, Chi
Zhang, Hong
Gao, Yanyang
author_sort Wang, Bo
title Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
title_short Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
title_full Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
title_fullStr Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
title_full_unstemmed Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
title_sort exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation
publishDate 2024
url https://hdl.handle.net/10356/178289
_version_ 1806059849534930944