The National Highway Traffic Safety Administration (NHTSA) uses data on the cost of roadway crashes to plan for highway safety and make decisions about where to allocate limited funds for roadway construction. They use data from several systems like FARS, GES, and NMVCCS to track and analyze the data.
Roadway classifications
To analyze this data, the NHTSA divides roadways into five categories:
- 4-lane divided roadways
- Greater than 4-lane divided roadways
- 2-lane undivided roadways
- Multi-lane undivided roadways
- All other roadways
The lane count in these categories includes lanes in both directions. These categories were chosen based on what is most useful for planning purposes.
FARS and GES systems
NHTSA uses data from two systems, FARS and GES, to track the location of crashes and identify the most severe injuries. They use this data to determine the proportion of crashes that happen on each roadway type and then apply this proportion to the total costs of urban and rural crashes.
MAIS and NMVCCS
- MAIS stands for “Maximum Injury Severity” and is a classification used by the NHTSA to indicate the most severe injury sustained by a person involved in a traffic accident.
- NMVCCS is another system used by NHTSA to determine whether the crash took place in an urban or rural area.
- FARS stands for Fatality Analysis Reporting System, it is a data system used by the NHTSA to track and analyze information about fatal traffic accidents in the United States. The FARS system collects detailed information about the crash, including information about the vehicles involved, the people involved, and the circumstances of the crash. The information is collected from police reports and other official sources, such as death certificates and hospital records. The data collected through FARS allows NHTSA to estimate the number of fatal crashes and the resulting fatalities that occur on public roads in the United States, which inform decisions about vehicle safety regulations and other safety measures.
- GES stands for General Estimates System, it is a data system used by the National Highway Traffic Safety Administration (NHTSA) to track and analyze the frequency, circumstances, and severity of injuries and property damage resulting from traffic accidents. The GES is a national probability sample of police-reported motor vehicle traffic crashes, providing annual data on the number of crashes and the resulting injuries and property damage. The GES is designed to provide a sample of crashes for all 50 states, the District of Columbia, and Puerto Rico. The data collected through GES allows NHTSA to estimate the number of crashes, injuries, and property damage that occur on public roads in the United States, which inform decisions about vehicle safety regulations and other safety measures.
Because GES records do not include an urban/rural designation, this feature was derived from the database we created from NMVCCS discussed above. NMVCCS cases were stratified within one of the five roadway designations for both urban and rural crashes. The proportions each roadway type that were urban and rural were calculated within each KABCO injury severity level. These proportions were then applied to each translated MAIS case total that was derived from the corresponding KABCO distribution.
For those of us who don’t know, KABCO is an acronym used by the National Highway Traffic Safety Administration (NHTSA) to classify the level of injury sustained by a person involved in a traffic accident. It stands for:
- K: killed (fatal injury)
- A: incapacitating injury (an injury that prevents the person from walking, driving, or performing other normal activities)
- B: non-incapacitating injury (an injury that doesn’t prevent the person from walking, driving, or performing other normal activities)
- C: possible injury (an injury that might have been sustained, but it’s not confirmed)
- O: no apparent injury (no visible injury)
The KABCO injury severity level is used in the GES data system by the NHTSA to track and analyze the severity of injuries resulting from traffic accidents. This helps inform decisions about vehicle safety regulations and other safety measures.
Injuries by Road Type (Rural vs Urban)
| A Injuries | Rural | Urban |
| Greater than four lanes divided | 13.11% | 86.89% |
| Multi-lane undivided | 26.63% | 73.37% |
| Four lanes divided | 64.59% | 35.41% |
| Two-lane undivided | 67.79% | 32.21% |
| Other | 37.20% | 62.80% |
| Total | 42.88% | 57.12% |
| B Injuries | ||
| Greater than four lanes divided | 14.14% | 85.86% |
| Multi-lane undivided | 13.14% | 86.86% |
| Four lanes divided | 43.27% | 56.73% |
| Two-lane undivided | 43.67% | 56.33% |
| Other | 14.30% | 85.70% |
| Total | 27.82% | 72.18% |
| C Injuries | ||
| Greater than four lanes divided | 9.42% | 90.58% |
| Multi-lane undivided | 12.70% | 87.30% |
| Four lanes divided | 24.34% | 75.66% |
| Two-lane undivided | 30.74% | 69.26% |
| Other | 10.11% | 89.89% |
| Total | 18.77% | 81.23% |
| Uninjured | ||
| Greater than four lanes divided | 23.14% | 76.86% |
| Multi-lane undivided | 14.82% | 85.18% |
| Four lanes divided | 67.71% | 32.29% |
| Two-lane undivided | 34.91% | 65.09% |
| Other | 20.19% | 79.81% |
| Total | 29.90% | 70.10% |
| Injured Severity Unknown | ||
| Greater than four lanes divided | 4.98% | 95.02% |
| Multi-lane undivided | 5.11% | 94.89% |
| Four lanes divided | 31.20% | 68.80% |
| Two-lane undivided | 0.79% | 99.21% |
| Other | 0.00% | 100.00% |
| Total | 4.72% | 95.28% |