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

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Virginia Tech


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.



Wet crash, hydroplaning, performance measure, skidding wet pavement, systemic crash analysis