Research on the causes of accidents with large trucks - a brief analysis (2023) (2023)

Federal Motor Carrier Safety Administration
Research and Analysis Office
Publication number FMCSA-RRA-07-017
July 2007

The Federal Motor Carrier Safety Administration (FMCSA) and the National Highway Traffic Safety Administration (NHTSA) conducted the Large Truck Collision Causes Study (LTCCS) to examine cause lb). A nationally representative sample of 120,000 serious truck accidents occurred between April 2001 and December 2003. Each accident in the LTCCS sample involved at least one large truck and resulted in one fatality.

The total LTCCS sample of 963 collisions included 1123 large trucks and 959 non-large trucks. There were 963 accidents, 249 people died and 1,654 people were injured. Of the 1,123 large trucks in the sample, 77% were tractors towing a semi-trailer and 5% were trucks transporting dangerous goods. Of the 963 collisions in the sample, 73% involved collisions between large trucks and at least one other vehicle.

define causality

Car accidents are complex events. They usually involve two or more cars. Factors that affect the occurrence of a fall can occur hours, days or months before the fall. This includes driver training and experience, vehicle design and manufacture, road and traffic light conditions, and weather conditions. Other factors may have occurred shortly before the accident, such as the decision to pull into traffic, a flat tire or snow. Crash reconstructionists rarely claim that the crash is the result of a single factor.

Fatigue, alcohol consumption and speeding are major contributors to motor vehicle accidents in general. While their presence does not always result in an accident, all three of these factors, along with other driver, vehicle, and environmental factors, increase the risk of an accident. In the LTCCS, "cause and effect" is defined in terms of the factors most likely to increase the risk of a large truck being involved in a serious accident.

data collection

Data from the 963 accidents in the LTCCS sample were collected in 24 locations in 17 states. Collision investigators and state truck inspectors travel to each accident location as soon as possible after the accident. Investigators gathered information about the accident scene through interviews with drivers, passengers and witnesses, and inspectors conducted a thorough examination of the truck, driver records and other documents. After leaving the scene of the accident, researchers collected more data by interviewing the truck driver or substituting for the driver if the real driver could not be interviewed. The investigators also reviewed police accident reports, hospital records, and the coroner's report, and re-examined the accident scene.

For each accident, data was collected on up to 1,000 elements, including the condition of the truck driver and other drivers involved prior to the accident; driver behavior during the collision; the condition of the truck and other vehicles; road surface factors; and climate conditions. Data is coded by accident experts, serious cases are reviewed by FMCSA and NHTSA staff, and completed cases are placed in an electronic database available to the public on the FMCSA website.

Estimates of national collapse

According to NHTSA estimates, there were approximately 120,000 fatal or injured accidents involving at least one large truck nationwide during the 33-month study period; these accidents involved 141,000 large trucks. Each of the 963 LTCCS case studies was assigned a sampling weight, allowing for a national estimate of the total number of truck accident victims during the study period.

All study results shown here are national estimates of the 141,000 large trucks NHTSA estimates were involved in fatal or injured accidents during the study period. Estimates may differ from actual values ​​because they are based on a sample of collision probabilities rather than a list of all collisions. The magnitude of the difference can vary depending on which LTCCS sample is the focus of a given table or analysis.

Encoding the crash cause variable

Many variables are encoded from the hundreds of data collected in each crash. Three main variables are coded for crash risk assessment:

Main events:An act or event that causes one or more vehicles to follow a course on which a collision is unavoidable. Critical events are assigned to vehicles that perform actions that make a collision unavoidable.

Main reasons:The immediate cause of the critical event (that is, the failure that led to the critical event). Assign severe causes to vehicles coded for severe collision events. It can be coded as driver errors, vehicle malfunctions, or environmental conditions (road or weather).
Relevant factors: Personnel, vehicles and environmental conditions at the time of the accident. It is not judged whether a factor is related to the cause of a specific collision, only whether the factor exists. The list of various factors that can be coded provides enough information to describe the circumstances of the accident.

key event

Three main types of critical events are attributed to large trucks:

• Lane exiting, entering another lane, or pulling off the road (32% of large trucks in the LTCCS sample were attributed to this critical event)
• Loss of vehicle control due to speeding due to road conditions, load changes, vehicle system failure, poor road conditions or other reasons (29%)
• Collision with the rear of another vehicle in a truck lane (22%).

main reason

The percentage of large trucks coded as serious causes depends on the type of collision:

Of the large trucks involved in all LTCCS accidents (single vehicle and multi-vehicle), 55% were named as the critical cause of the accident.
Of the large trucks involved in two-vehicle LTCCS collisions between a truck and a passenger vehicle (sedan, van, pickup truck, or SUV), 44 percent were designated as the critical cause.

Table 1 shows the main reasons attributed according to the main categories.

Note: Results shown are national estimates of the 141,000 large trucks involved in fatal accidents during the study period. Estimates may differ from actual values ​​because they are based on a sample of collision probabilities rather than a list of all collisions. Estimates are rounded to the nearest 1,000 large trucks.

The top causes for drivers fall into four categories:

• Inefficiency: The driver falls asleep, is incapacitated by a heart attack or seizure, or is physically incapacitated.
• Recognition: The driver is inattentive, distracted by things inside or outside the vehicle, or fails to observe the situation properly.
• Decision making: for example, the driver is driving too fast, misjudging the speed of another vehicle, or getting too close to another vehicle.
• Manifestations: For example, driver panic, overcompensation, or poor directional control.

relevant factor

Hundreds of correlation factors were collected for each vehicle in each accident. In descending order, the top 10 factors coded for large trucks and their drivers are:

• brake problem
• Traffic interruptions (congestion, previous accidents)
• use prescription drugs
• driving too fast for the conditions
• the road of ignorance
• road problem
• Must stop before collision (traffic control devices, crosswalks)
• use over-the-counter medications
• insufficient supervision
• fatigue.

relative risk

Relative risk analysis of data on the relevant factors using key events and key cause codes allows the classification of factors between those that occur only at the time of an accident and those that increase the risk of an accident. Trucks involved in LTCCS accidents can be divided into two groups: those designated as critical events and critical causes, and those without. By comparing the presence of associated factors coded into two groups, the relative risk for each factor can be estimated, as shown in the following example:

If 30% of trucks attributed as a cause of serious collisions are coded as the driver-related factor "going too fast for the conditions" and only 5% of trucks not attributed as a causative factor, it can be concluded that speed is a factor that increases the risk of being involved in a collision.
If 30% of trucks attributed as a cause of serious accidents were coded as the driver-related factor "use of prescription drugs" and 30% of trucks not attributed as a cause of serious accidents were also coded for the same related factor, then Conclusions: The use of prescription drugs is not a factor that increases the risk of traffic accidents.

Table 2 shows the 19 coded factors most commonly associated with large trucks in the LTCCS, where there was a statistically significant association between these factors and root cause attributions. The order of factors in the table is based on the number and percentage of trucks ranked for each factor. The relative hazard number is the major proportion coded because of factor-coded trucks to non-factor-coded trucks. Thus, Table 2 shows that a truck with brake problems was 170% more likely to be coded as a cause of a serious collision than a truck that was not coded as a factor associated with brake problems.

mesa 2

Correlation factors associated with large truck collisions and their relative risk importance

grades:Results presented are a national estimate of 141,000 large trucks involved in fatal or injured accidents during the study period. Estimates may differ from actual values ​​because they are based on a sample of collision probabilities rather than a list of all collisions. Estimates are rounded to the nearest 1,000 large trucks.

Three of the top 10 correlated factors coded for large trucks do not appear in Table 2. For the three associated factors – traffic interruptions, use of prescription drugs and the obligation to stop before the accident – ​​they did not differ significantly in the frequency of which trucks had and did not have these factors coded by the severity of the cause of the accident.

It is important to record the coding numbers of the factors involved and their relative hazard ratios. For example, the factor associated with braking problems was coded more frequently (29%) but had a lower relative hazard ratio than the other 13 factors. Only 4% of large truck accidents involving LTCCS were reported, with pre-crash load shifting having the highest relative hazard ratio (56.3).

Of the 19 factors listed in Table 2, 15 are drivers. The 15 pilots can be grouped into two broad categories. One group—fatigue, illness, and drug use (both legal and illegal)—reflected the driver's state before the accident. The second group - speeding, poor supervision, illegal driving, inattention, distraction (outside and inside the vehicle) and following too closely - reflected driving errors.

A large truck - collided with a passenger car

Half of LTCCS accidents involve collisions between large trucks and passenger vehicles (cars, pickup trucks, vans or SUVs). In these accidents, the same correlates that were most commonly coded for large trucks were also most commonly coded for passenger cars. For large trucks and passenger cars, the following 10 correlates, in descending order of how often they were coded as large trucks, had statistically significant relationships with the main cause codes:

• traffic interruption
• the road of ignorance
• insufficient supervision
• driving too fast in this situation
• illegal maneuver
• inattention
• fatigue
• illness
• Incorrect assumptions about the behavior of other road users
• Draw attention to objects or people inside the vehicle.

There are some important differences in the coding of relevant factors between the two vehicle types. For large trucks, but not for passenger cars, following too closely (traffic conditions that require stopping before crashing) and being distracted outside the vehicle were statistically associated with attribution of the main cause. In addition, vehicle factors (brakes, tires, blades, and load transfer) that were not coded or examined for passenger vehicles were statistically associated with attribution of root cause to large trucks.

For passenger cars, but not for trucks, alcohol and drug use was statistically associated with root cause coding. These factors, combined with fatigue (passenger cars coded twice as often as large trucks) and illness (passenger cars coded five times) Car drivers are more likely to be exposed to adverse physical conditions.

Research and data on the FMCSA website

You can learn more about the study on the causes of large truck collisionshereThe LTCCS homepage contains links to downloadable versions of public databases; user manuals; code books; 20 tables with sample data; reports to Congress; LTCCS Analysis Series reports research methods and application of research data for statistical analysis of crash risk; and an overview (PowerPoint) presentation of the survey results. For answers to specific questions, contact the FMCSA Department of Analytics at (202) 366-4039.