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Virginia Tech

Systemic Network-Level Approaches for Identifying Locations with High Potential for Wet and Hydroplaning Crashes

Abstract

dc:description.abstract

Crashes on wet pavements are responsible for 25% of all crashes and 13.5% of fatal crashes in the US (Harwood et al. 1988). This number represents a significant portion of all crashes. Current methods used by the Department of Transportations (DOTs) are based on wet over dry ratios and simplified approaches to estimate hydroplaning speeds. A fraction of all wet crashes is hydroplaning; although they are related, the difference between a "wet crash" and "hydroplaning" is a wet-crash hydrodynamic-based severity scale is less compared to hydroplaning where the driver loses control. This dissertation presents a new conceptual framework design to reduce wet- and hydroplaning-related crashes by identifying locations with a high risk of crashes using systemic, data-driven, risk-based approaches and available data. The first method is a robust systemic approach to identify areas with a high risk of wet crashes using a negative binomial regression to quantify the relationship between wet to dry ratio (WDR), traffic, and road characteristics. Results indicate that the estimates are more reliable than current methods of WDR used by DOTs. Two significant parameters are grade difference and its absolute value. The second method is a simplified approach to identify areas with a high risk of wet crashes with only crash counts by applying a spatial multiresolution analysis (SMA). Results indicate that SMA performs better than current hazardous-road segments identification (HRSI) methods based on crash counts by consistently identifying sites during several years for selected 0.1 km sections. A third method is a novel systemic approach to identify locations with a high risk of hydroplaning through a new risk-measuring parameter named performance margin, which considers road geometry, environmental condition, vehicle characteristics, and operational conditions. The performance margin can replace the traditional parameter of interest of hydroplaning speed. The hydroplaning risk depends on more factors than those identified in previous research that focuses solely on tire inflation pressure, tire footprint area, or wheel load. The braking and tire-tread parameters significantly affected the performance margin. Highway engineers now incorporate an enhanced tool for hydroplaning risk estimation that allows systemic analysis. Finally, a critical review was conducted to identify existing solutions to reduce the high potential of skidding or hydroplaning on wet pavement. The recommended strategies to help mitigate skidding and hydroplaning are presented to help in the decision process and resource allocation. Geometric design optimization provides a permanent impact on pavement runoff characteristics that reduces the water accumulation and water thickness on the lanes. Road surface modification provides a temporary impact on practical performance and non-engineering measures.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Civil Engineering
Department dc:contributor.department
Civil and Environmental Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2021

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Velez Rodriguez, Kenneth Xavier
Chair dc:contributor.committeechair
  • Flintsch, Gerardo W.
Committee members dc:contributor.committeemember
  • Blanco, Myra
  • Katicha, Samer Wehbe
  • Hancock, Kathleen

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:31999
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/104926

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Velez Rodriguez, Kenneth Xavier. Systemic Network-Level Approaches for Identifying Locations with High Potential for Wet and Hydroplaning Crashes. doctoral thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104926