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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 4. Intersection Applications

4.1 Running Red Light

This application area is intended to target crashes that result from signal violations. The running red light application provides a warning to drivers who are in danger of violating the signal.

4.1.1 Associated Pre-Crash Scenarios

The running red light application targets both the single-vehicle and multi-vehicle pre-crash scenario red light running. All of the crashes in this pre-crash scenario were considered potential targets for this application area.

4.1.2 Magnitude of Problem

There were an estimated 234,881 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was more than $13 billion (note that annual refers to 2005 through 2008).(1) Additionally, 45 percent of the target crashes resulted in fatalities or injuries.

4.1.3 Relevant Distributions

The distribution of target crashes by the six vehicle-type categories indicated that crashes involving two light vehicles represented 92 percent of the total crashes. All other vehicle types, including motorcycles, represented only a small portion (2 percent or less each) of the involved vehicles.

The distribution of target crashes by area type revealed that the majority of the crashes (78 percent) occurred in urban areas, and the remainder occurred in rural areas, indicating that signalized intersections are more prevalent in urban areas. The distribution of target crashes by posted speed limit indicated that the majority of the crashes (70 percent) occurred on roadways posted between 35 and 45 mi/h and were more prevalent in urban areas.

4.1.4 Relationships in HSIS Data

HSIS data from 2005 through 2007 were also investigated to determine the distribution of crash types by intersection traffic control.(2) While the NASS GES data indicated the magnitude of potential crashes impacted by the running red light application area, the HSIS analysis showed the magnitude of potential target crash types relative to other crash types at similar locations (i.e., the proportion of total signalized intersection collisions that could potentially be targeted by the application). There were 32,925 crashes identified at signalized intersections from the HSIS data in California from 2005 through 2007. The distribution by crash type showed that a large proportion of crashes at signalized intersections were broadside (angle), accounting for approximately 25.8 percent of crashes. A similar analysis was conducted for the 13,996 signalized intersection crashes from the HSIS data in Minnesota from 2005 through 2007. One of the leading crash types at signalized intersections was right-angle crashes, comprising 20.3 percent of signalized intersection crashes.

Of the 32,925 total crashes at signalized intersections in California from 2005 through 2007, 2,377 (7.2 percent) involved at least one heavy vehicle, and 775 (2.4 percent) involved at least one motorcycle. Fatal and severe injury crashes represented 1.9 percent of total crashes, 3.1 percent of heavy vehicle crashes, and 12.6 percent of motorcycle crashes at signalized intersections. Of those crashes involving at least one heavy vehicle at a signalized intersection, sideswipe crashes were the most prevalent (34.8 percent), followed by rear-end (28.6 percent) and broadside (18.9 percent). Of those crashes involving at least one motorcycle at a signalized intersection, broadside crashes were the most prevalent (28.4 percent), followed by rear-end (27.6 percent) and sideswipe (17.2 percent).

Of the 13,996 total crashes at signalized intersections in Minnesota from 2005 through 2007, 1,051 (7.5 percent) involved at least one heavy vehicle, and 153 (1.1 percent) involved at least one motorcycle. Similar to California, heavy vehicles and motorcycles were overrepresented in fatal and severe injury crashes at signalized intersections in Minnesota. Fatal and severe injury crashes represented 1.5 percent of total crashes, 2.3 percent of heavy vehicle crashes, and 11.1 percent of motorcycle crashes at signalized intersections. Of those crashes involving at least one heavy vehicle at a signalized intersection, rear-end crashes were the most prevalent (40.7 percent), followed by right-angle (18.9 percent) and sideswipe (18.8 percent). Of those crashes involving at least one motorcycle at a signalized intersection, rear-end crashes were the most prevalent (34.6 percent), followed by right-angle (18.3 percent) and other (18.3 percent).

4.2 Running Stop Sign

The running stop sign application area is intended to target crashes that result from stop sign violations at stop-controlled intersections. These intersections include two-way, four-way, and other stop-controlled intersections. The application provides a warning to drivers who are about to run a stop sign.

4.2.1 Associated Pre-Crash Scenarios

The running stop sign application area targets single-vehicle and multi-vehicle running stop sign pre-crash scenarios. All crashes in both scenarios are targeted for this application regardless of whether the intersection is two- or four-way stop-controlled. There are potentially other multi-vehicle crashes that result from a stop sign violation, but they were not coded as such by the police and are not included in these pre-crash scenarios. These crashes would have been included as straight crossing path at non-signals and turn at non-signals pre-crash scenarios. It is not possible to determine how many crashes in these pre-crash scenarios may be the result of stop sign violations versus other contributing factors, such as poor gap judgment; therefore, they were not counted in the estimate of targeted crashes. However, these pre-crash scenarios are targeted by the driver gap assistance at stop-control application addressed in section 4.4.

4.2.2 Magnitude of Problem

There were an estimated 44,424 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was more than $2.0 billion. Additionally, 45 percent of all the target crashes resulted in fatalities or injuries.

4.2.3 Relevant Distributions

The distributions of target crashes by the six vehicle-type categories were considered for both single-vehicle and multi-vehicle crashes (multi-vehicle crashes referred to the first two vehicles involved). Crashes involving light vehicles represented the majority for both single-vehicle and multi-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 multi-vehicle crashes (62 percent) occurred in urban areas, while the majority of single-vehicle crashes (59 percent) occurred in rural areas. This may highlight the need for different design considerations for applications in urban and rural areas.

4.2.4 Relationships in HSIS Data

HSIS data were investigated to determine the distribution of total crashes by intersection traffic control and area type.(2) While the NASS GES data indicated the magnitude of potential crashes impacted by this application, the HSIS analysis showed the prevalence of target intersections by area type and the magnitude of total crashes at those intersections. Based on the magnitude of total crashes at stop-controlled intersections, the HSIS intersection data analysis found that this application may be best targeted to two-way stop-controlled intersections. This was particularly true in rural areas, where crashes were more prevalent at two-way stop-controlled intersections compared to all-way stop-controlled intersections.

There were 35,758 crashes (51.7 percent of total) identified at two-way stop-controlled intersections from the HSIS data in California from 2005 through 2007. There were only 450 crashes (less than 1 percent of all intersection crashes) at all-way stop-controlled intersections in California. These results are based on total crashes (i.e., are not limited to specific crash types) and indicate the relative safety issue at two-way stop-controlled intersections when compared to all-way stop-controlled intersections.

A similar analysis identified 5,179 two-way stop-controlled intersection crashes (26.4 percent of total) from the HSIS data in Minnesota from 2005 through 2007. Similar to California, there were significantly fewer crashes (466 crashes, 2.4 percent of all intersection crashes) at all-way stop-controlled intersections. The distribution of two-way stop-controlled crashes in California and Minnesota by area type showed a large percentage (59.2 and 61.2 percent, respectively) of crashes in rural areas.

These results should be considered in the context of exposure. It may be expected that intersections with the greatest exposure (e.g., number of intersections and annual average daily traffic) will have the greatest number of crashes. In California and Minnesota, two-way stop-controlled intersections represented the greatest proportion of intersections from 2005 through 2007, accounting for 84 and 86 percent of all intersections in those States, respectively. All-way stop-controlled intersections accounted for less than 1 percent of all intersections by frequency and entering volume in both States. In California, both two-way and all-way stop-controlled intersections were more prevalent in rural areas, representing 73 percent of two-way stop-controlled intersections and 72 percent of all-way stop-controlled intersections. In Minnesota, two-way stop-controlled intersections were more prevalent in rural areas, accounting for 64 percent of all two-way stop-controlled intersections; however, all-way stop-controlled intersections were more prevalent in urban areas.

When compared to injuries at intersections with other traffic control types, two-way stop-controlled intersections in both California and Minnesota represented the greatest percentage of fatal and severe injury intersection crashes. In California, approximately 1.2 percent of two-way stop-controlled crashes resulted in fatalities, while 3.2 percent of these crashes resulted in severe injuries. In Minnesota, approximately 1.6 percent of two-way stop-controlled crashes resulted in fatalities, while 2.7 percent of these crashes resulted in incapacitating injuries.

Analysis of HSIS data by crash type showed a large number of angle and left-turn crashes at two-way stop-controlled intersections. The distribution by crash type in California indicated that 29.5 percent of crashes at two-way stop-controlled intersections were broadside (angle) type. California data did not include a specific crash type for left-turn crashes. Analysis of Minnesota data indicated that 49.7 percent of crashes at two-way stop-controlled intersections were right-angle crashes, and 6.8 percent were coded as left-turn crashes.

4.2.5 Potential Extension to Pedestrian and Bicycle Crashes

The running stop sign application area could potentially be extended to target vehicle-pedestrian crashes and vehicle-bicycle crashes at stop-controlled intersections. As a result, drivers would be warned of the presence of a crossing pedestrian or bicyclist, and pedestrians or bicyclists could be warned of a conflicting motor vehicle.

The single-vehicle pre-crash scenarios pedestrian/maneuver and bicyclist/maneuver were identified as target crashes for this application area. Specifically, the target crashes included crashes at stop-controlled intersections. Based on weighted GES data, there were an estimated 3,843 annual national target crashes, and the estimated total annual cost for these crashes was nearly $465 million.

4.3 Driver Gap Assist at Signalized Intersections

The driver gap assist at signalized intersections application area is intended to help drivers waiting to turn left at signalized intersections with permitted left turns through gap acceptance. The relevant crash type is a multi-vehicle crash involving a left-turning motor vehicle and a through motor vehicle.

4.3.1 Associated Pre-Crash Scenarios

This application targets the multi-vehicle pre-crash scenario left turn across path/opposite direction at signals. All of the crashes in this pre-crash scenario were considered potential targets for this application area. All crashes occurred at signalized intersections and involved a left-turning vehicle colliding with a through vehicle from the opposite direction. If the crash occurred because of a signal violation and not gap acceptance, it was included in a separate scenario.

4.3.2 Magnitude of Problem

There were an estimated 200,212 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was more than $10.3 billion. Additionally, 44 percent of all the target crashes resulted in fatalities or injuries.

4.3.3 Relevant Distributions

Considering only the first two vehicles involved, the distribution of target crashes by the six vehicle-type categories indicated that crashes involving two light vehicles represented 94 percent of the total crashes. All other vehicle types accounted for only a small portion (2 percent or less each) of involved vehicles.

The distribution of target crashes by area type indicated that the majority of the crashes (77 percent) occurred in urban areas, and the remainder (23 percent) occurred in rural areas. This distribution reflects the prevalence of signalized intersections in urban areas.

4.3.4 Relationships in HSIS Data

Analysis of HSIS intersection data by area type confirmed the NASS GES analysis findings, which indicated the potential to impact a large number of signalized crashes in urban areas through the driver gap assist at signalized intersections application area despite the HSIS bias toward rural roads. There were 32,925 crashes identified at signalized intersections from the HSIS data in California from 2005 through 2007. The distribution by area type showed that crashes at signalized intersections occurred more frequently in urban areas: 83.5 percent of signalized intersection crashes occurred in urban areas compared to 16.5 percent in rural areas. A similar analysis was conducted for the 13,996 signalized intersection crashes from the HSIS data in Minnesota from 2005 through 2007. The majority of signalized intersection crashes were also in urban areas: 85 percent of signalized intersection crashes occurred in urban areas compared to 14.6 percent in rural areas. The remaining 0.4 percent of crashes occurred in area types coded as "other."

These results should be considered in the context of exposure. In California, signalized intersections were more prevalent in urban areas, representing 79 percent of intersections by number and 85 percent by entering volume. Additionally, 83.5 percent of crashes at signalized intersections occurred in urban areas. There was a similar trend in Minnesota, where signalized intersections in urban areas represented 83 percent of intersections by number and 79 percent by entering volume, as compared to 85 percent of the crashes.

4.4 Driver Gap Assist at Stop-Controlled Intersections

The driver gap assist at stop-controlled intersections application area is intended to target crashes that result from poor gap acceptance at two-way stop-controlled intersections. These crashes include stop-controlled motor vehicles that are traveling straight or turning at an intersection. Gap acceptance, in this case, is defined as the process by which a driver on the minor road stops at the stop sign and then makes a maneuver (right or left turn) onto or across the major road. This process requires the driver to judge the speed of conflicting traffic and the adequacy of "gaps" in traffic to complete the maneuver.

4.4.1 Associated Pre-Crash Scenarios

The driver gap assist at stop-controlled intersections application area targets straight crossing path at non-signal and turn at non-signal multi-vehicle pre-crash scenarios, which include crashes at unsignalized intersections and driveways. This application area is targeted to the subset of crashes that occur at two-way stop-controlled intersections. Multi-vehicle crossing path crashes at two-way stop-controlled intersections can be classified as resulting from gap acceptance or stop sign violations. This application is intended for crashes resulting from poor gap acceptance and not from stop sign violations. The assumption is that the majority of cases in which the investigating officer coded the crash as a violation would involve a vehicle that failed to stop at the sign rather than a vehicle that stopped and then proceeded. Crashes resulting from stop sign violations (e.g., a driver is ticketed for violating a stop sign) were categorized in a separate pre-crash scenario, running stop sign.

4.4.2 Magnitude of Problem

There were an estimated 278,886 annual national target crashes based on weighted NASS GES data, and the estimated total annual cost of these crashes was nearly $18.3 billion. Additionally, 38 percent of the target crashes resulted in fatalities or injuries.

4.4.3 Relevant Distributions

Considering only the first two vehicles involved, the distribution of target crashes by the six vehicle-type categories indicated that crashes involving two light vehicles represented 93 percent of the total crashes. All other vehicle types represented only a small portion (2 percent or less each) of the involved vehicles. Crashes involving motorcycles accounted for 2 percent of multi-vehicle target crashes, which is slightly greater than the occurrence of motorcycles in all multi-vehicle crashes. Motorcycles represented 1.4 percent of all multi-vehicle crashes.

The distribution of target crashes by area type indicated that the majority of the crashes (68 percent) occurred in urban areas. Roadways with five or more approach lanes represented 34 percent of the crashes. This is particularly noteworthy because it underscores the need for assistance with gap acceptance when crossing wider approaches. Roadways with two approach lanes represented 46 percent of the crashes, which can likely be attributed to the prevalence of this lane configuration.

4.4.4 Relationships in HSIS Data

HSIS data were investigated to determine the distribution of crash severity by intersection traffic control. This application area addresses potentially severe crashes at two-way stop-controlled intersections. The HSIS data support that these intersections represent a greater percentage of fatal and severe crashes when compared to other intersections. Of the 35,758 crashes at two-way stop-controlled intersections in California from 2005 through 2007, 1,543 crashes (4.4 percent) were fatal or severe injury. There were relatively fewer fatal and severe injury crashes at signalized and all-way stop-controlled intersections in terms of both frequency and percentage. Of the 32,925 crashes at signalized intersections, 639 crashes (1.9 percent) were fatal or severe injury. Of the 450 crashes at all-way stop-controlled intersections, 14 crashes (3.1 percent) were fatal or severe injury.

A comparable analysis was conducted using the HSIS data in Minnesota from 2005 through 2007. Similar to California, the frequency and percentage of fatal and severe injury crashes were greater at two-way stop-controlled intersections than at signalized and all-way stop-controlled intersections. Of the 5,179 crashes at two-way stop-controlled intersections, 222 crashes (4.3 percent) were fatal or severe injury. There were 13,996 crashes at signalized intersections and 466 crashes at all-way stop-controlled intersections during the same period. Of these, 218 crashes at signalized intersections (1.5 percent) and 5 crashes at all-way stop-controlled intersection (1.1 percent) were classified as fatal or severe injury crashes.

Analysis of HSIS intersection data by area type showed the potential for this application area to be better targeted to rural areas; nearly 60 percent of crashes at two-way stop-controlled intersections in California occurred in rural areas. Similarly, 61.2 percent of crashes at two-way stop-controlled intersections in Minnesota occurred in rural areas.

Heavy vehicles and motorcycles should be considered in the design of this application. More than 9 percent of the crashes at two-way stop-controlled intersections from the California HSIS data involved at least one heavy vehicle, more than a quarter of which were broadside crashes. Similarly, approximately 4 percent of the two-way stop-controlled crashes involved at least one motorcycle, more than 30 percent of which were broadside crashes. These heavy vehicle and motorcycle crashes were more likely to result in a fatality than other crashes at two-way stop-controlled intersections. Similar distributions were also identified in the Minnesota data for heavy vehicles and motorcycles.

 

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