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Publication Number: FHWA-HRT-11-040
Date: November 2012

 

Crash Data Analyses for Vehicle-To-Infrastructure Communications for Safety Applications

Chapter 5. Speed Applications

5.1 Curve Speed Warning

The curve speed warning application area is intended to target crashes approaching horizontal curves on segments or interchange ramps that are speed-related. The application will provide a warning to drivers approaching a curve or ramp at an unsafe speed.

5.1.1 Associated Pre-Crash Scenarios

The curve speed warning application area targets several pre-crash scenarios including the following single-vehicle scenarios:

For both single-vehicle and multi-vehicle scenarios, speed-related crashes that occurred on a curve or an interchange ramp are targeted for this application.

5.1.2 Magnitude of Problem

There were an estimated 168,993 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was more than $29 billion. This included 146,906 crashes at curve locations and 22,086 crashes at interchange ramps. Additionally, 44 percent of the target crashes resulted in fatalities or injuries.

5.1.3 Relevant Distributions

The distributions of target crashes by the six vehicle-type categories were considered for both single-vehicle and multi-vehicle crashes, with the latter referring to the first two vehicles involved. The overwhelming majority of the crashes involved light vehicles as expected. Vehicles in the "other vehicles" category represented 6 percent of the single-vehicle crashes, while trucks (single-unit and combination-unit) represented 12 percent of the multi-vehicle crashes. Additionally, 5 percent of the target single-vehicle crashes involved motorcycles, which was approximately twice the occurrence of motorcycles in all single-vehicle crashes (2.7 percent). Motorcycles were also overrepresented in multi-vehicle crashes, accounting for 4.3 percent of the target crashes but only 1.4 percent of all multi-vehicle crashes.

The distribution of target curve crashes by area type was considered for both single-vehicle and multi-vehicle crashes. The number of curve crashes was greater in urban areas for both crash types when compared to rural areas. This was somewhat unexpected because single-vehicle crashes are generally a greater concern in rural areas.

The distribution of crashes by number of lanes and land use indicated that two-lane roadways represented the majority of crashes for single-vehicle urban crashes (70 percent), single-vehicle rural crashes (85 percent), multi-vehicle urban crashes (63 percent), and multi-vehicle rural crashes (74 percent).

5.1.4 Relationships in HSIS Data

HSIS data were explored from 2005 through 2007 in Illinois and Washington to develop measures of exposure for curves by area type. While there were generally more curves and miles of curves in rural areas (possibly due to the rural sampling bias), the vehicle-miles traveled on curves were greater in urban areas. Traditionally, single-vehicle lane-departure crashes, often associated with curves, are a concern in rural areas. However, this concern is usually based on comparisons of this crash type to other crash types on rural roads (not in comparison to urban areas). While intersection crashes are traditionally thought of as the major urban safety concern, these results indicated that curve crashes in urban areas can also benefit from the curve speed warning application area.

HSIS data were also investigated to determine the distribution of curves by degree of curve and severity. While the GES data indicated the magnitude of potential crashes impacted by speed advisory and warning approaching horizontal curves, the HSIS data were used to help identify the curves where most of the crashes occurred.

Although the frequency of crashes is greater for tangents when compared to curves, an analysis of HSIS curve data revealed that crashes on curves tend to be more severe than those on tangent segments of the roadway. In Washington, there were 31,419 crashes identified on curves and 113,303 crashes identified on tangents from the HSIS data from 2005 through 2007. Approximately 0.9 percent of the curve crashes resulted in a fatality, 2.3 percent resulted in an incapacitating injury, and 10.9 percent resulted in a non-incapacitating injury. These percentages were higher than the respective percentages for crashes on tangents: 0.4 percent fatal crashes, 1.7 percent incapacitating injury crashes, and 8.9 percent non-incapacitating injury crashes by comparison.

Degree of curve measures the sharpness of the curve and is inversely related to curve radius (the higher the degree, the sharper the curve). The degree of curvature category with the most severe injury crashes was 10.01 to 20.0 degrees. For this category, 1.2 percent of crashes resulted in a fatality, 3.4 percent resulted in an incapacitating injury, and 13.9 percent resulted in a non-incapacitating injury.

5.2 Work Zone Warning for Reduced Speed in Work Zones

The work zone warning for reduced speed in work zones application area is intended to target speed-related crashes in work zones. Speeding drivers will be provided with a warning in active work zones.

5.2.1 Associated Pre-Crash Scenarios

Speed-related crashes are not specific to any particular pre-crash scenario but are found in multiple scenarios. All pre-crash scenarios were considered targets for this application. Work zones were the only speed zones that could be explicitly identified in the NASS GES data.

5.2.2 Magnitude of Problem

There were an estimated 16,364 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was more than $1.3 billion. Additionally, 33 percent of the target crashes resulted in fatalities or injuries.

5.2.3 Relevant Distributions

Considering only the first two vehicles involved, the distribution of target crashes by the six vehicle-type categories indicated that crashes only involving light vehicles represented 86 percent of the total crashes. Additionally, 7 percent of single-vehicle target crashes involved combination-unit trucks, and 5 percent involved motorcycles. This was an overrepresentation of motorcycles by almost double because motorcycles only accounted for 2.7 percent of all single-vehicle crashes. All other vehicle types represented only a small portion (2 percent or less each) of the involved vehicles.

The distribution of target crashes by area type indicated that the majority of the crashes (55 percent) occurred in urban areas. Roadways with two lanes represented 46 percent of the crashes.

5.3 Spot Treatment/Weather Conditions

The spot treatment/weather conditions application area is intended to warn drivers to slow down for rain, ice, snow, or other adverse weather conditions that impact the roadway environment. These applications are envisioned to be applied to areas with a known history of weather-related crashes such as icy bridges or tangents in low-lying areas that flood during heavy rain.

5.3.1 Associated Pre-Crash Scenarios

The spot treatment/weather conditions application area targets crashes related to speeding during adverse weather conditions (based on both the surface conditions and the reported weather) for the single-vehicle and multi-vehicle pre-crash scenarios control loss/vehicle action and control loss/no vehicle action.

5.3.2 Magnitude of Problem

Based on weighted NASS GES data, there were an estimated 211,304 annual national target crashes, with an estimated total annual cost of $13.0 billion. Additionally, 28 percent of all the target crashes resulted in fatalities or injuries. (Note that these estimates include all locations, and targeting only selected locations decreases the estimates.)

5.3.3 Relevant Distributions

The distributions of target crashes by the six vehicle-type categories were considered for both single-vehicle and multi-vehicle crashes, with the latter referring to the first two vehicles involved. Vehicles in the "other vehicles" category represented 11 percent of the multi-vehicle crashes, while trucks (single- and combination-unit) represented 9 percent of the multi-vehicle crashes.

The distribution of target crashes by area type was considered for both single-vehicle and multi-vehicle crashes. The number of adverse weather crashes related to speeding was greater in urban areas for both single vehicle crashes (61 percent for urban) and multi-vehicle crashes (72 percent for urban) when compared to those in rural areas.

5.4 Speed Zone Warning

The speed zone warning application area is intended to warn drivers of reduced speed limits on tangents (e.g., on the approaches to small towns).

5.4.1 Associated Pre-Crash Scenarios

Speed-related crashes are not specific to any particular pre-crash scenario but are found in multiple scenarios. All pre-crash scenarios were considered targets for this application, and specific speed zones were used to identify target crashes. The NASS GES database does not explicitly identify speed zones. As a result, posted speed limits were analyzed for urban and rural locations based on statutory speed limits in the United States in section 11-802 of the Uniform Vehicle Code (UVC).(17) UVC establishes a statutory speed limit of 55 mi/h in locations other than urban districts and 35 mi/h in urban districts. Roadways with posted speed limits lower than these statutory speed limits may have been established as "speed zones." In this study, posted speed limits of 30 mi/h and under and 50 mi/h and under were considered speed zones for urban and rural areas, respectively, excluding interstate highway locations. It is likely that using this method for identifying speed zones overestimates the number of speed zones, therefore overestimating the target crashes.

5.4.2 Magnitude of Problem

There were an estimated 360,694 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was more than $28.5 billion. Additionally, 38 percent of the target crashes resulted in fatalities or injuries.

5.4.3 Relevant Distributions

Considering only the first two vehicles involved, the distribution of target crashes by the six vehicle-type categories indicated that crashes involving light vehicles represented 92 percent of single-vehicle crashes and 99 percent of multi-vehicle crashes. More than 4 percent of single-vehicle target crashes were motorcycles, which was an overrepresentation of motorcycles by almost double because they only accounted for 2.7 percent of all single-vehicle crashes. All other vehicle types represented only a small portion (2 percent or less each) of the involved vehicles.

The distribution of target crashes by area type indicated that the majority of the crashes (62 percent) occurred in rural areas. Roadways with two lanes represented more than half (56 percent) of the crashes.

 

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