Index
Documentation Page
Summary
Background
Methods
Results
Countermeasures
Tri-Level Comparison
Reference

Results

Causal Factors. Causal assessments were completed for 1239 (96.5 percent) of the drivers in the sample. There was insufficient data to complete causal assessments for 45 of the drivers. Of the 1284 drivers contained in the database, 507 (40.3 percent) were assessed as not contributing to crash causation. To demonstrate the relative importance of causal factor types, drivers who did not contribute to causation (507) and unknown values (45) were eliminated from the distribution. Proportions were then recomputed using the number of drivers who contributed to causation (732) as the denominator in subsequent calculations. The most frequently assigned causal factor groups are described below and shown in Figure 2.

  • DRIVER INATTENTION. The most dominant component of the causal factor pattern was driver inattention. As defined for this effort, driver inattention indicated a lack of focus on the required field of view (typically forward). This definition encompassed both of the driver inattention and driver distraction categories as defined in the earlier Indiana Tri-Level study (Treat, et al, 1979). Inattention was noted as the sole causal factor for 16.7 percent of the drivers who contributed to crash causation and was noted as the primary causal factor in combination with other contributory factors for 5.2 percent of the drivers. This factor was also cited as a contributory factor in combination with other primary factors for 0.8 percent of the drivers contributing to causation.

  • VEHICLE SPEED. The second largest component of the causal factor pattern was the vehicle speed factor. These assignments typically reflected circumstances in which the driver was exceeding the speed limit and the absolute vehicle velocity contributed to crash causation. It should be noted, however, that this causal factor was assigned in a small number of crashes where the vehicle’s travel speed was at or below the posted speed limit. In these situations, the travel speed was inappropriate for prevailing weather/roadway conditions and contributed to a pre-crash loss of vehicle control (i.e., too fast for conditions).

    Vehicle speed was assigned as the sole causal factor for 6.8 percent of the drivers who contributed to crash causation and was assigned as the primary factor in combination with other contributory factors for 3.8 percent of the drivers who contributed to causation. In addition, this factor was cited as a contributory factor in combination with other primary factors for 8.1 percent of the drivers.

  • ALCOHOL IMPAIRMENT. Alcohol impairment was the third largest component of the causal factor pattern. Driving while impaired by alcohol was the sole causal factor for 6.0 percent of the drivers who contributed to crash causation and was noted as the primary factor in combination with other contributory factors for 11.1 percent of the drivers who contributed to causation. In addition, alcohol impairment was cited as a contributory factor in combination with other primary factors for 1.1 percent of the drivers.

  • PERCEPTUAL ERRORS. The fourth most frequently assigned causal factor involved perceptual errors associated with intersection crashes. Two specific scenarios were noteworthy: (1) The subject driver checked for approaching traffic, did not see the other crash-involved vehicle (e.g., looked, did not see), and then attempted to cross or turn at the intersection. This factor was noted as the sole causation mechanism for 8.9 percent of the drivers who contributed to crash causation. (2) The driver checked for approaching traffic, saw the other vehicle, but then either misjudged the distance to that vehicle or misjudged the approach velocity of that vehicle (e.g., accepted inadequate gap to other vehicle). This factor was noted as the sole causation mechanism for 6.0 percent of the drivers who contributed to causation.

  • DECISION ERRORS. The primary scenario in this group involved subject drivers who attempted to turn or cross with an obstructed view (4.7 percent). While these situations typically reflected intersection crashes, there were a number of collisions which occurred at non-intersection locations (e.g., driver attempted to cross the roadway from a private/commercial driveway or attempted to turn into/exit a private/commercial driveway).

Additional causal factor types in this category included (1) violated a red traffic signal (2.6 percent), (2) attempted to beat a phasing signal (2.1 percent), and (3) violated a stop sign (0.7 percent). The total contribution of this category was 10.1 percent with all of the assignments occurring as primary/sole assignments.

  • INCAPACITATION. Drivers who fell asleep (4.4 percent) or experienced a seizure/heart attack/blackout (2.0 percent) also contributed to the causal factor pattern. All of the assignments in this category were made as primary/sole assignments (i.e., no contributory factors noted).

These six causal factor groups were assigned as primary (sole) factors for 60.9 percent of the drivers contributing to crash causation. These same factors were assigned as primary factors in combination with other contributing factors for an additional 20.2 percent of the drivers who contributed to crash causation. Thus, as primary assignments, these factors were assigned to 81.1 percent of the drivers who contributed to causation.

NOTE: Due to multiple causal factor assignments, proportions for individual causal factors add to more than 100.0.

Figure 2: Six Most frequently Assigned Causal Factor Groups

Crash Problem Types

In this multivariate analysis, important driver demographic/behavioral characteristics and crash situation descriptors associated with seven crash types were identified. The process involved eight major steps:

1. Produced and reviewed frequency distributions for each of the 203 variables contained in the combined NASS CDS/UDA data file.

2. Selected a set of 59 "Pattern" variables containing information useful for describing crashes in terms of UDAs and other crash, driver, vehicle, and road environment factors. Variables were selected from the following sources:

    • UDA variables - 46
    • NASS General Vehicle Form - 11
    • NASS Occupant Assessment Form - 2

3. Recoded selected pattern variables, combining response levels to simplify and improve the analysis.

4. Recoded NASS crash types (provided in Figure 3) to simplify and improve the analysis. Crash types were redefined into seven classes with operational differences that were likely to be associated with driver behavior/performance as follows:

    • Crash Type 1 - Single Driver, Right or Left Roadside Departure Without Traction Loss [NASS Types I: A (except 02), I: B (except 07), and I:C].

    • Crash Type 2 - Single Driver, Right or Left Roadside Departure With Traction Loss (NASS Types I: A-02 and I: B-07).

    • Crash Type 3 - Same Direction, Rear End (NASS Type II: D).

    • Crash Type 4 - Turn/Merge/Path Encroachment (NASS Types II: F and IV: J and K).

    • Crash Type 5 - Same Trafficway, Opposite Direction (NASS Type III: G, H, and I).

    • Crash Type 6 - Intersecting Paths, Straight Paths (NASS Type V: L).

    • Crash Type 7 - Other, Miscellaneous, Backing, Etc. (NASS Type VI: M).

    • NASS Crash Type II: E did not occur in the UDA data file.

5. Determined unweighted frequencies for each of the 59 pattern variables, treating each driver/vehicle as a unit of analysis. Cross tabulations of unweighted observations of each pattern variable with crash type were then constructed.

6. Calculated a relative involvement index to assess the over-and-under representation of each profile variable within each crash type. Tables were prepared showing the frequency, percentage, and relative involvement in six of the 59 pattern variables within the seven defined crash types.

Crash Types as Identified in the NASS Program

Figure 3: Crash Types as Identified in the NASS Program.

7. Selected a limited set of six "key" profile variables (from the original set of 59 pattern variables) to characterize crash scenarios within crash types. The key variables which frequently had high indices of over-representation included crash cause, BAC test result, primary behavior source, necessary UDA, travel speed, and first UDA in sequence. Another set of more general variables including driver age, sex road surface condition, and lighting was also examined to further characterize specific scenario types.

8. Determined the most frequent scenarios within each crash. In general, it was noted that combinations of four of the six key variables noted in the preceding step resulted in the most homogenous and distinctive scenario groupings. Specifically, BAC test result and travel speed were excluded from the cross-tabulations. For Crash Type 3: Same Direction; Rear End crashes, however, it was necessary to include the travel speed variable to achieve adequate distinction between the scenario types.

A prioritized listing of crash problem types identified by this analysis sequence is provided in Table 1. The 23 problem types shown in this table comprised 43.2 percent of the UDA crash sample. These same problem types contributed to an additional 25.2 percent of the crashes in the sample when they were combined with a broad range of other factors. Therefore, the problem types in Table 1 contributed to more than two-thirds of the UDA sample crashes.

Table 1

Prioritized Listing of Crash Problem Types

 

Crash Type

Problem Type

% of UDA Sample

3. Same Direction, Rear End

1. Driver Inattention - Mid Range Speeds

2. Driver Inattention - Low Range Speeds

3. Driver Inattention - High Range Speeds

4. Following Too Closely - High Range Speeds

5.6

2.5

2.4

2.4

4. Turn, Merge, Path Encroachment

1. Looked, Did Not See

2. Accepted Inadequate Gap To Other Vehicle

3. Turned With Obstructed View

4. Driver Inattention/TCD Violation

4.1

3.3

2.3

2.3

2. Single Driver, Right or Left Roadside Departure With Traction Loss

1. Excessive Vehicle Speed

2. DUI/DWI With Excessive Speed

3. DUI/DWI

2.3

1.6

1.6

1. Single Driver, Right or Left Roadside Departure Without Traction Loss

1. Driver Fatigue

2. Driver Inattention

3. DUI/DWI

1.7

1.6

1.5

6. Intersecting Paths, Straight Paths

1. Looked, Did Not See

2. Driver Inattention/TCD Violation

3. Crossed With Obstructed View

1.6

1.3

1.2

5. Same Trafficway, Opposite Direction

1. Driver Inattention

2. Lost Directional Control

3. Excessive Vehicle Speed

0.9

0.9

0.8

7. Other, Miscellaneous

1. Excessive Vehicle Speed

2. Following Too Closely

3. Sudden Deceleration

0.5

0.4

0.4

 

Total

43.2

 

Key characteristics of crash problem types are summarized in Tables 2 through 8. The presentation sequence is as follows:

 

Table No.

 

Crash Type

 

Problem Type

 

% of UDA Sample

2

 

Same Direction, Rear End

 

1-4

 

12.9

3

 

Turn, Merge, Path Encroachment

 

1-4

 

12.0

4

 

Single Driver, Roadside Departure With Traction Loss

 

1-3

 

5.5

5

 

Single Driver, Roadside Departure Without Traction Loss

 

1-3

 

4.8

6

 

Intersecting Paths, Straight Paths

 

1-3

 

4.1

7

 

Same Trafficway, Opposite Direction

 

1-3

 

2.6

8

 

Other, Miscellaneous

 

1-3

 

1.3

         

Total

43.2

Table 2

Same Direction, Rear End Crashes (Problem Types 1-4)

Crash Problem Type

Key Characteristics

1. Driver Inattention -

Mid Range Travel Speeds

5.6 Percent of UDA Sample

  • Subject driver was inattentive to the driving task and struck the rear of a lead vehicle.
  • Subject vehicles were initially traveling at speeds of 49-72 km/h (30-45 mph).
  • Crashes typically occurred on urban/suburban arterial roadways during periods of moderately heavy traffic densities.
  • Crashes occurred during daylight hours and clear weather conditions.
  • Inattention mechanisms were varied and included looking at buildings/pedestrians (22.7 percent), traffic in adjoining lanes, (3.2 percent), traffic signs (3.2 percent), approaching traffic, (9.7 percent), retrieving objects (3.2 percent), and focusing on internal thought processes (9.7 percent).
  • Younger drivers (<35 years) were over-represented (80 percent) and younger male drivers, in particular were over-represented (52 percent).
  • Drivers admitting to inattention did not attempt to shift crash responsibility.

2. Driver Inattention -

Low Range Travel Speeds

2.5 Percent of UDA Sample

  • Subject driver was inattentive to the driving task and struck the rear of a lead vehicle.
  • Subject vehicles were initially traveling at speeds of 25-48 km/h (15-29 mph).
  • Two scenarios were identified. In the most frequently occurring scenario (76 percent), the subject driver was traveling on urban/suburban surface street and in the second scenario the subject driver was traveling on an entrance ramp to an expressway/interstate roadway.
  • Nearly all crashes occurred during daylight hours, in clear weather conditions, and in heavy traffic densities.
  • Drivers in the ramp scenario were inattentive as a result of focusing on traffic in the through lanes. Inattention mechanisms for drivers on surface streets were varied and included looking at buildings (5.3 percent), adjusting cassette player (5.3 percent), conversing with passengers (15.8 percent), looking at approaching traffic (5.3 percent), looking in rear view mirror (26.1 percent), focusing on internal thought processes (5.3 percent).
  • Younger drivers (<35 years) were over-represented (61 percent) in this problem type.
  • Drivers did not attempt to shift crash responsibility.

3. Driver Inattention -

High Range Travel Speeds

2.4 Percent of UDA Sample

  • Subject driver was inattentive to the driving task and struck the rear of a lead vehicle.
  • Subject vehicles were initially traveling at speeds of 73-96 km/h (46-60 mph).
  • Crashes occurred on arterial roadways during daylight hours, in clear weather, and during periods of moderate to heavy traffic densities.
  • Inattention mechanisms included looking at traffic in an adjoining lane (20.0 percent), conversing with passengers (10.0 percent), and focusing on internal thought processes (30.0 percent).
  • Older drivers (>55 years) appeared to be over-represented (30 percent).
  • Approximately 40 percent of drivers attempted to shift crash responsibility.

4. Following Too Closely High Range Travel Speeds

2.4 Percent of UDA Sample

  • General characteristics duplicated preceding scenarios with the exception that the subject driver struck the lead vehicle as a result of following too closely.
  • Subject vehicle struck lead vehicle while it was still moving.
  • Male drivers were over-represented in the sample.
  • Subject drivers shifted crash responsibility to the lead vehicle.

Table 3

Turn, Merge, Path Encroachment Crashes (Problem Types 1-4)

Crash Problem Type

Key Characteristics

1. Looked, Did Not See

4.1 Percent of UDA Sample

  • Subject driver did not see other crash involved vehicle.
  • 90 and 180 degree approach trajectory scenarios identified.
  • Intended left turn across path of other vehicle or into path of other vehicle.
  • Occurred at intersections controlled by stop sign - 90 degree scenario.
  • Occurred at intersections controlled by traffic signal - 180 degree scenario.
  • Small proportion occurred at commercial accesses - entering (180 degree) exiting (90 degree).
  • Occurred during daylight hours and clear weather conditions.
  • 90 degree scenario occurred in light traffic densities - 180 degree scenario occurred in full range of densities.
  • Older drivers over-represented [(25 percent >70 years of age), (50 percent >55 years of age)].
  • Drivers in the 35-54 year age group appeared to be involved as a result of an inappropriate traffic scanning technique.
  • Younger drivers (<35 years) were also over-represented and appeared to be involved as a result of completing perfunctory traffic checks.
  • Accepted crash responsibility.

2. Accepted Inadequate Gap To Other Vehicle

3.3 Percent of UDA

Sample

  • Driver noted presence of other vehicle, but misjudged the distance to that vehicle or the approach velocity of that vehicle.
  • 90 and 180 degree approach trajectory scenarios identified.
  • Primarily left turn across path of approaching vehicle. Small portion of 90 degree scenario drivers initiated a right turn into the path of the approaching vehicle.
  • Occurred at intersections controlled by a stop sign - 90 degree scenario.
  • Occurred at intersections controlled by a traffic signal - 180 degree scenario.
  • Occurred during daylight hours and clear weather conditions.
  • 90 degree scenario occurred in light traffic densities - 180 degree scenario occurred in full range of traffic densities.
  • Younger drivers (<35 years) over-represented in 90 degree scenario (86 percent) - associated with aggressive driving traits.
  • Older drivers over-represented in 180 degree scenario with 21 percent exceeding age 70 and 42 percent exceeding age 55.
  • Older male and younger female drivers shifted crash responsibility.

3. Turned With

Obstructed View

2.3 Percent of UDA

Sample

  • Intervening non-contact vehicle blocked subject drivers view of other crash-involved vehicle.
  • 90 and 180 degree approach trajectory scenarios identified.
  • Subject driver initiated left turn across path of other vehicle.
  • Occurred at intersections controlled by a stop sign - 90 degree scenario.
  • Occurred at intersections controlled by a traffic signal - 180 degree scenario.
  • Occurred during daylight hours, in clear weather conditions, and in moderate to heavy traffic densities.
  • Younger drivers (<35 years) over-represented in 90 degree scenario (56 percent) with no evidence of aggressive driving.
  • Older drivers were over-represented in 180 degree scenario with 46 percent exceeding the age of 55 and 23 percent exceeding the age of 70.
  • Older male drivers and female drivers tended to shift crash responsibility to the other driver.

4. Driver Inattention/

TCD Violation

2.3 Percent of UDA Sample

  • Subject driver was inattentive to driving task and violated TCD.
  • 90 and 180 degree approach trajectory scenarios identified.
  • Subject driver either violated a TCD and struck a left turning vehicle or violated a TCD, turned left, and was struck by the other crash-involved vehicle.
  • Most TCD violations involved traffic signals (85 percent), occurred during daylight hours, in clear weather conditions, and during a range of traffic densities.Inattention mechanisms were varied and included looking for street signs (7.1 percent), conversing with passengers (7.1 percent), and focusing on internal thought processes (28.6 percent).
  • Younger male drivers (<35 years) were over-represented (42.9 percent) as were males in general (85 percent).

Table 4

Single Driver, Roadside Departure With Traction Loss Crashes (Problem Types 1-3)

Crash Problem Type

Key Characteristics

1. Excessive Vehicle Speed

2.3 Percent of UDA Sample

  • Subject driver was typically approaching a curve (76.5 percent) while exceeding the speed limit by more than 24 km/h (15 mph). As a result of this travel speed, vehicle exited the roadway.
  • Most of the crashes occurred on local or collector roadways (64.7 percent) during periods of darkness (58.8 percent) and during clear weather 88.2 percent)
  • Younger males (<35 years) were over-represented (65.4 percent) with males less than 20 years of age comprising 46.2 percent of the sample.
  • Most drivers attempted to shift crash responsibility to a variety of design characteristics or roadway condition factors.

2. DUI/DWI With

Excessive Vehicle Speed

1.6 Percent of UDA Sample

  • All of the subject drivers were classified as DUI or DWI.
  • These drivers were typically approaching a curve (76.5 percent) while exceeding the speed limit by more than 24 km/h (15 mph) - 53 percent.
  • As a result of the alcohol and vehicle speed factors, the subject drivers lost directional control and exited the roadway.
  • Most of the crashes occurred on local or collector roadways (64.7 percent) during periods of darkness (76.5 percent) and during clear weather conditions (88.2 percent).
  • Younger drivers (<35 years) were over-represented (58.8 percent) in the age distribution.
  • Most drivers attempted shift crash responsibility to roadway design characteristics, roadway condition factors, or visibility limitations.

3. DUI/DWI Crashes

1.6 Percent of UDA Sample

  • With the exception of the vehicle speed factor, all other aspects of this problem type either duplicated or paralleled characteristics in the preceding problem type.

Table 5

Single Driver, Roadside Departure Without Traction Loss Crashes (Problem Types 1-3)

Crash Problem Type

Key Characteristics

1. Driver Fatigue

1.7 Percent of UDA

Sample

  • Subject driver fell asleep departing the roadway to the left or right.
  • Drivers were typically completing short duration local trips.
  • Crashes typically occurred during the hours of darkness (56.3 percent) with the most of the night crashes occurring between 2 am and 5 am.
  • All of the crashes that occurred in daylight hours involved workers coming home from work or traveling to work. All of these drivers reported sleep deprivation in the preceding 24 hour period.
  • Younger males (<35 years) were over-represented in the age distribution (68.9 percent).
  • All of the subject drivers admitted falling asleep and did not attempt to shift crash responsibility.

2. Driver Inattention

1.6 Percent of UDA

Sample

  • Subject driver became inattentive and allowed the vehicle to drift off the roadway to the left or right.
  • Crashes typically occurred during daylight hours, in clear weather conditions, and during periods of light traffic densities.
  • Inattention mechanisms included adjusting radio/reaching into ash tray (28.6 percent) conversing with passengers (14.3 percent), checking baby passenger (7.1 percent), reaching into purse (14.3 percent), and retrieving/lighting cigarette (7.1 percent).
  • Younger female drivers (<35 years) were over-represented in the age distribution (42.9 percent).
  • Most drivers in this crash type did not attempt to shift crash responsibility.

3. DUI/DWI Crashes

1.5 Percent of UDA

Sample

  • Subject driver exited the roadway as a result of a DUI/DWI circumstance.
  • Most of the crashes occurred on local or collector roadways during periods of darkness with the highest proportion occurring between midnight and 5 am (53.6 percent).
  • Crashes were often associated with vehicle speed. Specifically, the driver was exceeding the speed limit in 50.0 percent of these crashes.
  • Younger male drivers (<35 years) were over-represented (42.9 percent) as were male drivers between the ages of 35-54 (35.7 percent).
  • Drivers typically did not admit to consuming alcoholic beverages prior to crash occurrence.

Table 6

Intersecting Paths, Straight Paths Crashes (Problem Types 1-3)

Crash Problem Type

Key Characteristics

1. Looked, Did Not See

1.6 Percent of UDA

Sample

  • All crashes occurred at intersection locations where the subject vehicle was controlled by a stop sign.
  • Approach trajectories were initially separated by 90 degrees.
  • Both drivers intended to proceed straight through the intersection.
  • The other crash-involved vehicle was typically approaching from the subject driver’s right (71.4 percent). The subject driver did not see this vehicle and accelerated into the intersection.
  • Older drivers were over-represented with 35.7 percent of the drivers exceeding the age of 70 and 42.8 percent exceeding the age of 55.
  • Drivers between 35 and 54 years of age appeared to be involved as a result of using inappropriate traffic scanning techniques. Younger drivers (<35 years ) were involved as a result of performing perfunctory traffic checks.
  • Drivers did not attempt to shift crash responsibility.

2. Driver Inattention/

TCS Violation

1.3 Percent of UDA

Sample

  • All crashes occurred at intersection locations that were typically controlled by traffic signals (80 percent).
  • Approach trajectories of involved vehicles were initially separated by 90 degrees.
  • Due to inattention to the driving task, subject driver violated TCD and entered intersection.
  • Crashes occurred during daylight hours and clear weather conditions.
  • Inattention mechanisms included looking for street address (10.0 percent), hanging up cell phone (10.0 percent), conversing with passenger (10.0 percent), and focusing on internal thought processes (20.0 percent).
  • All of the drivers in the sample were less than 35 years of age.
  • Drivers did not attempt to shift crash responsibility.

3. Crossed With Obstructed

View

1.2 Percent of UDA

Sample

  • All crashes occurred at intersection locations where the subject vehicle’s direction of travel was controlled by a stop sign.
  • Approach trajectories of involved vehicles were initially separated by 90 degrees.
  • Other vehicle was most frequently approaching from the subject driver’s right (57 percent).
  • Subject driver’s view of approaching vehicle was blocked by intervening vehicle.
  • All crashes occurred during daylight hours and during periods of moderate to moderately heavy traffic densities.
  • Sample size was limited, but males in the 35-54 year age group appeared to be over-represented.
  • Drivers did not attempt to shift crash responsibility.

Table 7

Same Trafficway, Opposite Direction Crashes (Problem Types 1-3)

Crash Problem Type

Key Characteristics

1. Driver Inattention

0.9 Percent of UDA

Sample

  • Trajectories of involved vehicles were initially 180 degrees opposed.
  • The subject driver became inattentive to the driving task and allowed the subject vehicle to drift into the opposing traffic lane.
  • The subject vehicle most frequently struck the side of the other vehicle (36.4 percent) or was struck in the side by the other vehicle (33.3 percent). The remaining crashes were either head-on configurations or off-set frontal configurations.
  • Most crashes occurred during daylight hours and clear weather conditions (87.5 percent) and during periods of light traffic densities.
  • Inattention mechanisms included reaching for tools on seat (9.1 percent), conversing with passengers (9.1 percent), checking delivery log, (9.1 percent), retrieving object from left floor pan (9.1 percent), reading magazine (9.1 percent), and focusing on internal thought processes (9.1 percent).
  • Younger drivers (<35 years) were over-represented in the age distribution (70 percent).
  • More than half of the drivers attempted to shift crash responsibility.

2. Lost Directional Control

0.9 Percent of UDA

Sample

  • The subject driver lost directional control while traversing a wet or icy surface and crossed into the opposing travel lane.
  • Most of the drivers were traveling within the speed limit (92.9 percent), however, the travel speed was inappropriate for given weather/road surface conditions.
  • The most frequent impact configurations were front to side (42.9 percent), off-set frontal (35.7 percent), and head-on (14.3 percent).
  • Younger female drivers (<35 years) were over-represented (38.5 percent) as were male drivers between the age of 35 and 54 (30.8 percent).
  • Most drivers accepted crash responsibility.

3. Excessive Vehicle Speed

0.8 Percent of UDA

Sample

  • Subject drivers lost directional control while traveling on dry surfaces as a result of excessive vehicle speed.
  • Subject vehicles crossed into opposing travel lanes and were involved in head-on or off-set frontal impact configurations.
  • Clinical sample size was insufficient to establish the range of situational characteristics. All the drivers in the sample, however, were less than 35 years of age.

Table 8

Other, Miscellaneous Crashes (Problem Types 1-3)

Crash Problem Type

Key Characteristics

1. Excessive Speed

0.5 Percent of UDA

Sample

  • Subject vehicles were involved in a wide array of unusual impact configurations.
  • The common thread tying these crashes together was involvement of the subject vehicle due to excessive speed.
  • The clinical sample size was insufficient to establish the range of situational characteristics or demographic characteristics.

2. Following Too Closely

0.4 Percent of UDA

Sample

  • Subject vehicles were involved in a wide array of unusual impact configurations.
  • The subject vehicle’s crash involvement could be traced to following too closely behind a lead vehicle.
  • The clinical sample size was insufficient to establish the range of situational characteristics or demographic characteristics.

3. Sudden Deceleration

0.4 Percent of UDA

Sample

  • Subject vehicles were lead vehicles that decelerated suddenly due to a non-contact vehicle crossing its intended travel path.
  • Sudden deceleration steering/braking inputs resulted in a misalignment between the lead and following vehicles such that a nominal rear end crash configuration was changed to a front to side impact configuration.
  • The clinical sample size was insufficient to establish the range of situational characteristics or demographic characteristics.

There were several other interesting findings as a result of these analyses. Some of these are described below.

  • Despite the fact that 732 drivers committed some behavioral error or unsafe driving act, only 418 drivers (57 percent) were charged with any violation by the police. Of the drivers receiving citations from the police, 18 percent were for failure to yield, 17 percent for driving while impaired, 10 percent for violating stop signs or traffic signals, 7 percent for reckless driving, and 4 percent for speeding violations.

  • Almost one-third of the drivers in the sample (29 percent) indicated that they were unaware of the impending collision and did not recognize any need for evasive action.

  • Close to one-third of the turning/intersection crashes (32 percent) occurred at locations where there were no traffic control devices reflecting the large number of cases where drivers were turning into private driveways or commercial accesses.

  • Approximately 79 percent of the primary unsafe driving acts reflected a deliberate intent of the driver to engage in that action. Most of the unintentional acts were associated with "driver inattention" and "looked but did not see" behavioral errors.

  • The source of the driver behavioral errors in these crashes was distributed as follows:

    Driver Decision 59 percent
    Driver Inattention 27 percent
    Driver Perception 12 percent
    Driver Motor Skills 2 percent