# Presentation: 334315

## Examination of Crash Contributing Factors

***Brittany N. Campbell***
- Campbellb@volpe.dot.gov
- Volpe National Transportation Systems Center
- Research and Special Programs Administration
- U.S. Department of Transportation

- National Intelligent Vehicle Initiative Meeting
- Washington, D.C.
- June 25-26, 2003

**Notes:**
Work was done as part of the Volpe Center’s effort in supporting the Light Vehicle IVI platform
The research presented is the result of discussion and advice from Dr. David Smith, Director of the LV platform from NHTSA

## Presentation Outline

- Objective
- Target Crash Types and Subtypes
- Analysis of Crash Contributing Factors
- Concluding Remarks

**Notes:**
In order to better determine the performance specifications and the anticipated benefits for collision avoidance systems, a thorough analysis of the critical event dynamics and the crash contributing factors is needed.  This research focuses on three crash types and provides an analysis of crash contributing factors, a cross-correlation of CFs, and primary contributing factors for each crash type.  

Crash data for this analysis was obtained from the National Automotive Sampling System (NASS) 2000 General Estimates System (GES).

To begin this afternoon’s presentation I will first state the objective of the light vehicle research and then move into a detailed description of the target crash types and subtype definitions used.  Next I will provide an overview of the analysis preformed and then finish with some concluding remarks.

## Objective

- Obtain a better picture of crash contributing factors to:
- Develop and prioritize countermeasure functions for crash warning systems
- Estimate potential safety benefits

**Notes:**
The objective of the current research was to:

## Light Vehicle Crash Distribution

**Based on 2000 General Estimates System Data**

**Notes:**
In 2000, there were approximately 6.4 million (6,394,000) PR motor vehicle crashes based on 2000 GES estimates.  
Of these, as many as 6.1 million (6,133,000) or 96 percent involved at least 1 light vehicle. 

The above figure shows the distribution of PR light vehicle crashes for 2000.   light vehicles include passenger cars, sport utility vehicles, vans , and pickup trucks. The four dominant crash types are rear-end, crossing path, off roadway, and lane change. Together these four crash types have a combined frequency of 85% (5,241,000) of all PR Light vehicle crashes 

This analysis examines rear-end, off-roadway, and lane change crashes
An analysis of crossing path crashes was conducted by Virginia Tech as part of a project to develop performance guidelines for signal and stop sign violation warning systems 

“Other” crashes are the sum of crashes with objects, undefined crashes, and other crashes not classified as any of the above types.

## Target Crash Subtypes

**Based on 2000 General Estimates System Data**

**Notes:**
-  The target crashes were split into 2 subtypes: towed due to damage and not towed due to damage.
The light green bars represents crashes that were not towed due to damage.  These include vehicles that were driven from the scene and those   that were towed from the scene for other reasons besides damage.
-  Rear-end crashes were defined as crashes in which the front of the following vehicle strikes the rear of a lead vehicle.  Both vehicles must be traveling in the same lane
Restricted to 2 vehicle crashes, striking vehicle must be a LV
-  Single vehicle off-roadway crashes were defined as crashes in which vehicle leaves roadway as first harmful event.  This crash type does not include cases of roadway departure that result from a collision.
Restricted to single vehicle crashes, LV
-  Lane Change crashes were defined as crashes in which vehicle attempts to change lanes, merge, pass, turn, leave/enter a parking position, or drifts & strikes, or is struck by another vehicle in the adjacent lane.  Both vehicles are traveling in the same direction
Restricted to 2 vehicle crashes, vehicle which initiated the maneuver must be a LV
-  The results presented are from the 2000 General Estimates System.  The GES presents a nationally represented sample of approximately 55,000 police-reported crashes a year.  Information is available for all types of crashes involving all types of vehicles.  
-  The 2 subtypes (towed due to damage and not towed due to damage) were chosen since another part of the research conducted involved comparing the GES to the Crashworthiness Data System or CDS.  The CDS is restricted to crashes involving at least one LV towed from the scene due to damage.  
-  In the above figure the CDS would provide the information for the towed due to damage cases.  For the case of this presentation only the GES was examined.
-  Note that the majority of the RE and LC crashes were not towed due to damage, whereas in the SVOR crash type the Towed due to Damage was the predominate subtype.

## Crash Analysis

- Crash Contributing Factors
- Severity Analysis
- Cross-correlation of Contributing Factors
- Primary Crash Contributing Factors

**Notes:**
Four types of crash analysis will be presented
The first will be Crash contributing factors for the target crashes determined from an in-depth examination of the CDS and GES crash databases.  A total of eleven crash contributing factors were identified from the GES.  
Next, a severity analysis will be presented to show how the CF were affected by the crash severity
It is known that a number of factors often contribute to a crash, to identify prevalent combinations of factors for each crash type
a cross-correlation of the CF’s was conducted 
Finally, a priority scheme will be used to identify one primary CF for each crash

## Crash Contributing Factor Analysis

- Towed vs. Not Towed (Rear-end)

**Based on 2000 General Estimates System Data**

**Notes:**
Results of the Contributing factor analysis for RE crashes.  Crashes involving a LV towed from the scene due to damage are shown in blue, all other crashes are in green. Relative frequencies represent that the factor was present in x% of the RE crashes

95th percentile confidence intervals were added to the figure.  

A total of 11 CFs were analyzed from the GES.  Note that adverse environmental conditions were not considered as a contributing factor to the crash.  Everyday people drive in adverse conditions and do not get into a crash.  Rather AEC were examined as a possible variable in the crash.  The existence of adverse conditions may or may not have been a factor in the crash.  

Adverse environmental conditions were defined as not occurring in daylight (lighting condition), not occurring on dry pavement (roadway surface condition), and not occurring in clear weather (atmospheric condition).  If any of these three conditions were met the crash was considered to occur in adverse conditions.

Vehicle defects and speeding were each split into two factors.  One resulting in a loss of control and the other as a contributing factor to the crash.  

The top two CF for RE crashes were inattention and Speeding as a contributing factor.

## Crash Contributing Factor Analysis

- Towed vs. Not Towed (Single Vehicle Off-roadway)

**Based on 2000 General Estimates System Data**

**Notes:**
The 3 leading crash contributing factors for SVOR crashes are inattention and speeding as a contributing factor and resulting in a control loss.  
Speeding as a CF encompasses all control loss cases due to excessive speed (travel speed>speed limit) it does not include control loss cases due to speeding on poor roadway conditions.
Impaired drivers (alcohol/drugs, ill/blackout, and sleepy/drowsy) also contributed to a large percentage of the crashes

Note... hit and run in crashes involving 1 towed vehicle.  Hit and run may also involve a driver that fled the scene

## Crash Contributing Factor Analysis

**Crash Contributing Factor Analysis**

- Towed vs. Not Towed (Lane Change)

**Based on 2000 General Estimates System Data**

**Notes:**
Similar to RE crashes inattention was a CF for a large portion of the crashes.  Speeding was the 2nd leading CF for vehicle stowed from the scene and hit and run was 2nd for vehicles not towed.

Impairment was not as large of a factor as in SVOR crashes.  Rather most LC crashes occurred due to inattention, speeding, and vision obstructions.

Due to the current interest in driver inattention the following slide provides a detailed breakdown of the inattention crashes.

## Distribution of Driver Inattention

| Driver Inattention | Rear-end | Single Veh. Off-roadway | Lane
Change |
| --- | --- | --- | --- |
| Look/Did Not See | 4% | 1% | 11% |
| Dist. By Other Occupant | 1% | 1% | 0% |
| Dist./Moving Object | 0% | 0% | 0% |
| Talk Cell Phone | 1% | 0% | 0% |
| Adj. Climate Control | 0% | 0% | 0% |
| Adj. Radio/CD | 1% | 1% | 0% |
| Use Object Integral | 0% | 0% | 0% |
| Use Object Brought | 2% | 2% | 0% |
| Dist. By Outside | 3% | 0% | 0% |
| Eating/Drinking | 1% | 0% | 0% |
| Smoking Related | 0% | 0% | 0% |
| Dist./Lost in Thought | 48% | 20% | 35% |
| Other Distraction | 5% | 10% | 4% |
| TOTAL | 66% | 35% | 50% |
| Based on 2000 data; LV towed due to damage. |  |  |  |

**Notes:**
Crash frequencies are presented for the distribution of Driver Inattention Towed due to damage crashes.
Inattention is most dominate in RE crashes.  66% of RE crashes involved driver inattention, compared to 50% of LC and 35% of SVOR.

Note that even though the GES cites inattention as a contributing factor in a large percentage of the crashes, the majority of the inattention cases are lumped in distracted/lost in thought category.  

i.e., The CDS provides more detailed information on  particular distractions

## Severity Analysis

|  | Contributing Factors |  |
| --- | --- | --- |
| Crash Type | More Severe Crashes | Less Severe Crashes |
| Single Vehicle Off-roadway | Alcohol/drugs | Successful Evasive Maneuver |
|  | Sleepy/drowsy | Hit & Run |
|  | Speeding (CF) |  |
| Rear-end | Alcohol/drugs | Hit & Run |
|  | Sleepy/drowsy |  |
|  | Vehicle Defect (CF) |  |
|  | Speeding (CF) |  |
| Lane Change | Sleepy/drowsy | Hit & Run |
|  | Speeding (CL) |  |
|  | Speeding (CF) |  |

**Based on 2000 General Estimates System Data**

**Notes:**
-  Using the crash contributing factors an analysis was conducted on the effect that the crash severity has on the factors.
-  Severe crashes were defined as crashes in which at least one light vehicle was towed from the scene due to damage. Cases where the vehicle was driven from the scene or towed from the scene not due to damage were classified as less severe.  
-  Variances between severe and less severe crashes were analyzed to see if there was a statistically significant difference between the contributing factors.  
-  Generally speaking, crashes with contributing factors alcohol/drugs, speeding, and sleepy/drowsy tend to be more severe.
-  The strong correlation of alcohol/drugs with the crash severity reflects the current trend found in the Fatality Analysis Reporting System crash database.  The FARS reports that 40% of all fatal crashes in 2000 involved alcohol.  
-  The speed that the vehicle is traveling prior to the impact also has a direct correlation to the severity of the crash.
As the speed of the vehicle increases, the driver has less time to perform an evasive action and the damage to the vehicle also increases, resulting in higher injury and fatality rates for the occupants.  
-  Similar to drivers under the influence of alcohol/drugs, the ability of drivers to react to an impending situation is greatly impaired if they are  Sleepy/drowsy.  Drivers are less likely to be able to avoid the collisions or at least perform an evasive maneuver to reduce the severity of the collision.  
-  Hit and Run crashes tended to be less severe

## Cross-correlation Analysis

- Correlation of *Inattention* with Other Factors
- (Single Vehicle Off-roadway ~ Towed Due to Damage)

**Notes:**
Collisions are often caused by more than one factor.  Cross-correlation charts were created to account for the crash contributing factors in scenarios that involve multiple factors.  

For the example shown, Inattention was cited in 35% of all SVOR Towed crashes
Both inattention and alcohol/drugs were contributing factors in 5% of all SVOR towed crashes
Both inattention and ill/blackout were contributing factors in 1% of SVOR towed crashes
The relative frequencies presented refer to the total crash population not just the inattention crashes.

It is possible for one crash to have 3 or more CF’s.  For example a crash with CF’s inattention, alcohol/drugs, and AEC would be represented three times in the figure.  Once in inattention, once in inattention and alcohol/drugs, and once in inattention and AEC.  

## Priority Scheme

- Alcohol/drugs
- Ill/blackout
- Sleepy/drowsy
- Vehicle Defect (CL)
- Vehicle Defect (CF)
- Inattention
- Driver’s Vision Obscured
- Speeding (CL)
- Speeding (CF)
- Successful Evasive Maneuver
*Adverse Environmental Conditions*
- Hit & Run

**Notes:**
-  Looking at the cross correlation charts it is clear the collisions are often caused by multiple factors.  The interrelationship between the factors is important to understand, however it is also important to determine a primary contributing factor for each case.  By determining the distribution of the primary contributing factors better collision countermeasures can be developed.
-  A priority scheme was used to break down the cases with multiple factors and assign one contributing factor that overrides the others.  
The factors are positioned in descending order by their degree of influence on a possible collision and their ability to be addressed by a crash warning system 
-  The first 3 factors all represent the incapacitation or impairment of the driver.  These factors clearly take precedence over all other factors.  Within the incapacitation /impairment grouping , the factors were ranked based on their effect on the other factors.  Alcohol/drugs was positioned at the top of the ranking.  Since it is possible that a driver may blackout as a result of alcohol/drugs; therefore, alcohol/drugs takes precedence over ill/blackout.
The process continues in a descending order through factor 10.  The first 10 factors in the priority scheme were used to provided information on the primary factor of the collision.  Using the priority scheme, cases coded as having one of the first 10 primary factors were extracted from the group of target crashes.  Information about the factors on the remaining target crashes was not available; therefore each case was examined to see if adverse environmental conditions existed at the time of the collisions.  Since minimal information on hit and run crashes was available, the factor was places after AEC.  By placing this factor last crashes with know AEC were accounted for in the AEC variable, thus reducing the amount of unknown information.
-  As stated earlier AEC were not considered as a contributing factor, they were rather examined as a variable to a crash. 

NOTES:
All remaining cases not linked to any of the contributing factors were put into an “undetermined” category
Unknowns not redistributed; put into “undetermined” category
Amount of “undetermined” crashes ranged from 12-35% (CDS) and 7-34% (GES)
4th and 5th factors grouped together as vehicle defect.  In the cases of a defective vehicle a collision or evasive maneuver is likely to occur no matter how, for example, attentive the driver is.  

## Primary Contributing Factors

| Towed Due to Damage | SVOR | RE | LC |
| --- | --- | --- | --- |
| Alcohol/drugs | 21% | 8% | 7% |
| Ill/Blackout | 2% | 0% | 0% |
| Sleepy/drowsy | 6% | 1% | 0% |
| Vehicle Defect (CL) | 3% | 0% | 1% |
| Vehicle Defect (CF) | 2% | 2% | 1% |
| Inattention | 14% | 35% | 26% |
| Driver’s Vision Obscured | 2% | 2% | 1% |
| Speeding (CL) | 27% | 1% | 8% |
| Speeding (CF) | 5% | 8% | 2% |
| Successful Evasive Maneuver | 0% | 0% | 0% |
| Adverse Environmental Conditions | 11% | 16% | 19% |
| Hit and Run | 0% | 0% | 1% |
| Undetermined | 7% | 27% | 34% |
| TOTAL: | 100% | 100% | 100% |

**Based on 2000 General Estimates System Data**

**Notes:**
The primary contributing factors for the towed due to damage crashes are presented above.  For example for SVOR crashes ... first all crashes were examined for the CF alcohol/drugs, these cases were extracted , next the remaining crashes were examined for signs of an ill/blackout driver, and so on done through the list.
All remaining cases not linked to any of the contributing factors were put into an “undetermined” category

Alcohol/drugs, inattention, and speeding remain the top three factors.
Since only one factor was assigned to each cases the sum of the distribution adds to 100% ensuing that each crash was only counted once.

## Concluding Remarks

- Dominant Contributing Factors
- Effect of Crash Severity on Contributing Factors
- Contribution of Multiple Factors to Crashes
- Dominant Primary Contributing Factors

**Notes:**
1. For the investigated crash subtypes, the dominant contributing factors were inattention and speeding both resulting in a control loss and as a CF

2. A few of the crash contributing factors were found to be effected by the crash severity. Generally speaking, crashes with contributing factors alcohol/drugs, speeding, and sleepy/drowsy tend to be more severe.  And hit and run crashes tended to be less severe.

3. The cross-correlation analysis proved the theory the crashes are often caused by multiple factors.  Furthermore, crashes are rarely caused by one single factor.  The factors alcohol/drugs, inattention, and speeding were found to be highly correlated.

4. The top primary contributing factor varied between the three crash types, however the top three factors remained steady.  Alcohol/Drugs, Inattention, and Speeding either as a control loss or as a contributing factor to the crash.

## Slide 16

## Comparison of CDS and GES

**Inattention**

**Alcohol/drugs**

**Speeding (Control Loss)**

**Notes:**
A comparison was conducted using the crash contributing factors from the CDS to see how they match with the results from the GES.  
The most variance between the two databases was found in the inattention and speeding resulting in a control loss contributing factors.  As noted earlier the GES cited more cases than the CDS as involving an inattentive driver.  However, the CDS had more information on the exact type of inattention than the GES.  

In comparison of the contributing factor speeding, it was found that speeding was a CF in more crashes in the GES than in the CDS for the SVOR and LC crash types.  For the RE crash type both databases cited 1% of the crashes.  The variance between the 2 databases is understandable in for this factor since the GES codes the crashes from the police accident reports.  

The results for the contributing factor alcohol/drugs match very well between the CDS and GES.  

Overall you can see that Inattention is a large factor in RE and LC crashes, and Speeding and Alcohol/drugs are predominant in SVOR crashes.

Remind audience the CDS is from 4 years.  So there could be other hidden factors that may explain why the databases do not match