Fatal Crashes Only

This report covers fatal crashes only, from the NHTSA Fatality Analysis Reporting System — the federal census of every crash on a US public road that killed someone within 30 days. It does not include injury or property-damage-only crashes, and its totals are not comparable with the all-severity crash reports published elsewhere on this site.

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Monthly Traffic Safety Analysis

116 CRASHES IN
TENNESSEE
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

In September 2023, Tennessee recorded 116 fatal crashes, a decrease from 131 fatal crashes in September 2022. This represents an 11.45% reduction in fatal crash events year-over-year. The total number of fatalities also decreased by 11.8%, from 144 in the prior period to 127 in the current period.

116

-11.5%was 131

Total Crash Events

127

-11.8%was 144

Persons Killed

72

-20.9%was 91

Persons Injured

9

-25.0%was 12

Hit-and-Run Crashes

Note: "Persons Killed" (127) counts individual fatalities across all crash events. "Fatal" in the severity table below (116) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Fatal crashes in Tennessee saw a notable downward trend year-over-year, decreasing from 131 fatal crashes in September 2022 to 116 fatal crashes in September 2023. This 11.45% reduction in fatal crash events was accompanied by an 11.8% decrease in total fatalities, from 144 to 127, indicating an overall improvement in traffic safety outcomes for the month.

9

Hit-and-Run Crashes — September 2023

-25.0% vs prior (12)

The number of fatal hit-and-run crashes decreased from 12 in September 2022 to 9 in September 2023. The hit-and-run rate also saw a decline, moving from 9.2% of all fatal crashes in the prior period to 7.8% in the current period. This indicates a downward trend in fatal crashes involving hit-and-run incidents.

Vulnerable Road User Casualties

21

Pedestrians Killed

Prior: 26-19.2%

3

Cyclists Killed

Prior: 4-25.0%

103

Motorists Killed

Prior: 113-8.8%

1

Pedestrians Injured

Prior: 2-50.0%

0

Cyclists Injured

Prior: 00.0%

71

Motorists Injured

Prior: 88-19.3%

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for fatal crashes shifted from Saturday with 25 fatal crashes in the prior period to Friday with 23 fatal crashes in the current period. The peak hour also changed, moving from 4 PM with 12 fatal crashes in September 2022 to 7 PM with 13 fatal crashes in September 2023. This suggests a shift in when fatal crashes are most concentrated.

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Road & Environmental Conditions

Clear weather remained the dominant condition for fatal crashes, accounting for 103 fatal crashes in the current period, down from 116 in the prior period. Fatal crashes occurring in rainy conditions decreased from 5 to 2 year-over-year, while fog conditions, not reported in the prior period, contributed to 4 fatal crashes in the current period. Regarding lighting, daylight fatal crashes decreased from 63 to 50, while fatal crashes in dark-not lighted conditions remained stable at 31 for both periods.

Weather

Clear103 (89.6%)
-11.2%prior 116
Cloudy6 (5.2%)
0.0%prior 6
Fog, Smog, Smoke4 (3.5%)
Rain2 (1.7%)
-60.0%prior 5

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight50 (43.1%)
-20.6%prior 63
Dark - Lighted31 (26.7%)
6.9%prior 29
Dark - Not Lighted29 (25.0%)
-6.5%prior 31
Dusk3 (2.6%)
Dark - Unknown Lighting2 (1.7%)
Reported as Unknown1 (0.9%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Lighting condition field

Vehicles & Demographics

Among the top vehicle makes involved in fatal crashes, Chevrolet saw a decrease from 30 in the prior period to 17 in the current period. Nissan/Datsun and Toyota both increased from 13 vehicles in the prior period to 15 vehicles in the current period. Harley-Davidson motorcycles also saw a slight decrease from 13 to 12 vehicles involved in fatal crashes.

Top Vehicle Makes (173 vehicles)

1
FORD20 (11.6%)
-9.1%prior 22
2
CHEVROLET17 (9.8%)
-43.3%prior 30
3
NISSAN/DATSUN15 (8.7%)
15.4%prior 13
4
TOYOTA15 (8.7%)
15.4%prior 13
5
JEEP / KAISER-JEEP / WILLYS- JEEP12 (6.9%)
33.3%prior 9
6
HARLEY-DAVIDSON12 (6.9%)
-7.7%prior 13
7
GMC9 (5.2%)
12.5%prior 8
8
HONDA9 (5.2%)
-35.7%prior 14
9
KIA7 (4%)
-12.5%prior 8
10
UNKNOWN MAKE6 (3.5%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Vehicle unit records

6 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (252 persons with recorded sex)

Male171 (67.9%)
-19.7%prior 213
Female81 (32.1%)
-20.6%prior 102

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

The highest number of fatal crashes occurred in the 55 mph speed zone, with 31 fatal crashes in the current period, a decrease from 33 in the prior period. Fatal crashes in the 45 mph zone also decreased from 31 to 29. Conversely, fatal crashes in the 30 mph zone increased from 6 in the prior period to 12 in the current period, representing a doubling in this speed category.

Fatal crashes by zone: 25 mph: 2 of 2 (100%) · 30 mph: 12 of 12 (100%) · 35 mph: 11 of 11 (100%) · 40 mph: 17 of 17 (100%) · 45 mph: 29 of 29 (100%) · 50 mph: 7 of 7 (100%) · 55 mph: 31 of 31 (100%) · 65 mph: 3 of 3 (100%) · 70 mph: 4 of 4 (100%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Posted speed limit at crash location

Manner of Collision

The dominant manner of fatal collision for both periods was 'The First Harmful Event was Not a Collision with a Motor Vehicle in Transport,' accounting for 73 fatal crashes (62.9%) in the current period, down from 77 fatal crashes (58.8%) in the prior period. Angle collisions decreased from 26 fatal crashes to 22, while Front-to-Front collisions slightly increased from 15 to 16 fatal crashes.

Manner of Collision

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Vehicle Type

The leading vehicle body type involved in fatal crashes was the 4-door sedan, remaining stable at 49 vehicles for both periods. Light pickup trucks saw a significant decrease from 41 vehicles in the prior period to 21 in the current period. Two-wheel motorcycles also decreased from 23 to 20 vehicles involved in fatal crashes year-over-year.

Vehicle Type

1
4-door sedan, hardtop49 (28.3%)
2
Compact Utility (Utility Vehicle Categories "Small" and "Midsize")25 (14.5%)
3
Light Pickup21 (12.1%)
4
Two Wheel Motorcycle (excluding motor scooters)20 (11.6%)
5
Station Wagon (excluding van and truck based)8 (4.6%)
6
Large utility (ANSI D16.1 Utility Vehicle Categories and "Full Size" and "Large")8 (4.6%)
7
Unknown body type6 (3.5%)
8
Minivan (Chrysler Town and Country, Caravan, Grand Caravan, Voyager, Voyager, Honda-Odyssey, ...)6 (3.5%)
9
Truck-tractor (Cab only, or with any number of trailing unit; any weight)6 (3.5%)

Showing top 9 of 23 reported. 14 additional (24 total) not shown: 2-door sedan,hardtop,coupe, Single-unit straight truck or Cab-Chassis (GVWR range 10,001 to 19,500 lbs.), 5-door/4-door hatchback, Utility station wagon (includes suburban limousines, Suburban, Travellall, Grand Wagoneer), 3-door/2-door hatchback, Medium/heavy Pickup (GVWR greater than 10,000 lbs.), Single-unit straight truck or Cab-Chassis (GVWR greater than 26,000 lbs.), Motor Scooter, Three-wheel Motorcycle (2 Rear Wheels), Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), Farm equipment other than trucks, Unenclosed Three Wheel Motorcycle / Unenclosed Autocycle (1 Rear Wheel), Convertible(excludes sun-roof,t-bar), Auto-based pickup (includes E1 Camino, Caballero, Ranchero, SSR, G8-ST, Subaru Brat, Rabbit Pickup).

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Vehicle unit records

Rural vs Urban

Fatal crashes in urban areas slightly decreased from 74 in the prior period to 73 in the current period. Rural fatal crashes saw a more substantial decrease, falling from 57 in the prior period to 43 in the current period. In the current period, rural areas accounted for 37.1% of fatal crashes, down from 43.5% in the prior period, highlighting a continued, albeit reduced, disproportionate share of fatalities in rural settings.

Rural vs Urban

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Roadway Functional Class

In the current period, Minor Arterial roads accounted for the most fatal crashes with 35, a slight decrease from 37 in the prior period. Principal Arterial roads (Other Principal Arterial in current, Principal Arterial - Other in prior) saw a decrease from 47 fatal crashes to 33. Conversely, fatal crashes on Local roads increased from 11 in the prior period to 17 in the current period.

Roadway Functional Class

1
Minor Arterial35 (30.2%)
2
Other Principal Arterial33 (28.4%)
3
Local17 (14.7%)
4
Major Collector12 (10.3%)
5
Interstate10 (8.6%)
6
Minor Collector8 (6.9%)
7
Other Freeways and Expressways1 (0.9%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Roadway Ownership

State Highway Agencies continued to oversee the highest number of fatal crashes, with 76 in the current period, a decrease from 93 in the prior period. City or Municipal Highway Agencies saw a decrease from 24 to 18 fatal crashes. County Highway Agencies, however, experienced an increase in fatal crashes from 14 in the prior period to 20 in the current period.

Roadway Ownership

1
State Highway Agency76 (65.5%)
2
County Highway Agency20 (17.2%)
3
City or Municipal Highway Agency18 (15.5%)
4
National Park Service1 (0.9%)
5
State Park, Forest, or Reservation Agency1 (0.9%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Person Type

Drivers were the most frequently involved person type in fatal crashes, decreasing from 201 in the prior period to 172 in the current period. Passengers also saw a decrease from 84 to 58. Pedestrians involved in fatal crashes decreased from 28 to 22, while bicyclists decreased from 4 to 3.

Person Type

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Person Injury Severity

The number of fatal injuries (K) decreased from 144 in the prior period to 127 in the current period. Persons with no injuries (O) also decreased from 86 to 58. The number of serious (A) and minor (B) injuries remained stable at 25 for both periods, while possible (C) injuries decreased from 29 to 17.

Person Injury Severity

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Occupant Safety Equipment

The use of 'Shoulder and Lap Belt Used' decreased from 162 persons in the prior period to 133 persons in the current period. The number of persons recorded with 'None Used/Not Applicable' safety equipment also decreased from 87 to 64. This indicates a general reduction across both categories of safety equipment usage among those involved in fatal crashes.

Occupant Safety Equipment

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Point of Impact

The '12 Clock Point' (front) remained the dominant area of impact in fatal crashes, though it decreased from 114 instances in the prior period to 98 in the current period. Impacts at the '3 Clock Point' (right side) saw a decrease from 13 to 6. Conversely, impacts at the '1 Clock Point' increased from 13 to 15, and at the '9 Clock Point' (left side) from 5 to 7.

Point of Impact

"Other" combines 8 smaller categories (17 records): Non-Collision (4), 2 Clock Point (3), Undercarriage (3), 7 Clock Point (2), 10 Clock Point (2), Other Objects or Person Set-In-Motion (1), Left-Front Side (1), 4 Clock Point (1).

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Vehicle unit records

Vehicles Per Crash

Single-vehicle fatal crashes remained relatively stable, decreasing slightly from 68 in the prior period to 67 in the current period. Two-vehicle fatal crashes saw a notable decrease from 51 to 38. Fatal crashes involving three vehicles increased from 8 to 9, while those with four vehicles decreased from 3 to 2.

Vehicles Per Crash

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-09-01 to 2023-09-30 · Crash-level records

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from NHTSA FARS (Fatal Crashes), accessed programmatically via the NHTSA FARS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: NHTSA FARS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2023-09-01 through 2023-09-30
  • Report generated: August 5, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: Tennessee
  • Total crash records analyzed: 116
  • Total persons involved: 257
  • Total vehicles involved: 173

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "Tennessee Crash Intelligence Report: September 2023." Published August 5, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: NHTSA FARS (Fatal Crashes), NHTSA FARS Open Data. Available at: https://thatcarhitme.com/crash-data/tennessee/fatal/statewide/september-2023-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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