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.

SponsoredThatCarHitMe.com

If someone you love is part of this data, call us.

We'll connect you with a vetted California attorney who handles fatal-crash and wrongful death cases and will evaluate whether you have a case.

(888) 988-8341Free for accident victims

Monthly Traffic Safety Analysis

315 CRASHES IN
CALIFORNIA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

In September 2023, California experienced 315 fatal crashes, a decrease of 11.76% compared to 357 fatal crashes in September 2022. This resulted in 334 fatalities, down 12.34% from 381 fatalities in the prior year. A notable shift was observed in motorcycle crashes, which increased by 18.52% year-over-year.

315

-11.8%was 357

Total Crash Events

334

-12.3%was 381

Persons Killed

202

-18.9%was 249

Persons Injured

44

4.8%was 42

Hit-and-Run Crashes

Note: "Persons Killed" (334) counts individual fatalities across all crash events. "Fatal" in the severity table below (315) 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

Overall, fatal crashes in California decreased year-over-year, with a reduction of 42 fatal crashes, from 357 to 315. Similarly, total fatalities declined by 47, moving from 381 in the prior period to 334 in the current period, indicating a downward trend in both metrics.

44

Hit-and-Run Crashes — September 2023

4.8% vs prior (42)

Fatal hit-and-run crashes increased from 42 in the prior period to 44 in the current period. Consequently, the hit-and-run rate rose from 11.8% to 14% of all fatal crashes. This indicates an upward trend in the proportion of fatal crashes involving a hit-and-run incident.

Vulnerable Road User Casualties

104

Pedestrians Killed

Prior: 114-8.8%

11

Cyclists Killed

Prior: 13-15.4%

212

Motorists Killed

Prior: 246-13.8%

7

Other Killed

Prior: 8-12.5%

6

Pedestrians Injured

Prior: 9-33.3%

2

Cyclists Injured

Prior: 0%

194

Motorists Injured

Prior: 240-19.2%

0

Other Injured

Prior: 00.0%

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 Friday in the prior period to Saturday in the current period, with both days recording 64 fatal crashes. The peak hour for fatal crashes remained 8 PM, experiencing a slight increase from 29 fatal crashes in the prior period to 31 in the current period.

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 conditions continued to be associated with the majority of fatal crashes, accounting for 272 in the current period compared to 317 in the prior period. Fatal crashes occurring in daylight decreased from 133 to 115, and those in dark-lighted conditions also saw a reduction from 107 to 96. There was no change in road surface conditions as data was not available for either period.

Weather

Clear272 (88.0%)
-14.2%prior 317
Cloudy34 (11.0%)
21.4%prior 28
Rain2 (0.6%)
-66.7%prior 6
Blowing Sand, Soil, Dirt1 (0.3%)

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

Lighting

Daylight115 (36.6%)
-13.5%prior 133
Dark - Lighted96 (30.6%)
-10.3%prior 107
Dark - Not Lighted84 (26.8%)
-12.5%prior 96
Dawn7 (2.2%)
-22.2%prior 9
Dusk7 (2.2%)
-12.5%prior 8
Dark - Unknown Lighting5 (1.6%)

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

Vehicles & Demographics

Toyota remained the most frequently involved vehicle make in fatal crashes, though its count decreased from 79 in the prior period to 60 in the current period. Honda moved into the second position with 48 vehicles, while Ford's involvement decreased from 51 to 42 vehicles. Notably, Harley-Davidson motorcycles saw an increase in fatal crash involvement, from 18 to 23.

Top Vehicle Makes (474 vehicles)

1
TOYOTA60 (12.7%)
-24.1%prior 79
2
HONDA48 (10.1%)
0.0%prior 48
3
CHEVROLET43 (9.1%)
-10.4%prior 48
4
FORD42 (8.9%)
-17.6%prior 51
5
NISSAN/DATSUN28 (5.9%)
-9.7%prior 31
6
HARLEY-DAVIDSON23 (4.9%)
27.8%prior 18
7
DODGE20 (4.2%)
-23.1%prior 26
8
BMW18 (3.8%)
80.0%prior 10
9
UNKNOWN MAKE13 (2.7%)
-13.3%prior 15
10
YAMAHA12 (2.5%)
20.0%prior 10

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

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

Sex Distribution (752 persons with recorded sex)

Male538 (71.5%)
-9.6%prior 595
Female214 (28.5%)
-23.0%prior 278

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

Fatal crashes at 55 mph experienced a decrease from 88 in the prior period to 64 in the current period, and crashes at 65 mph also fell from 82 to 52. In contrast, fatal crashes at 45 mph increased from 30 to 44, and those at 35 mph rose from 42 to 48. This suggests a shift in crash distribution towards lower speed zones.

Fatal crashes by zone: 5 mph: 1 of 1 (100%) · 15 mph: 1 of 1 (100%) · 20 mph: 1 of 1 (100%) · 25 mph: 15 of 15 (100%) · 30 mph: 18 of 18 (100%) · 35 mph: 48 of 48 (100%) · 40 mph: 34 of 34 (100%) · 45 mph: 44 of 44 (100%) · 50 mph: 17 of 17 (100%) · 55 mph: 64 of 64 (100%) · 60 mph: 1 of 1 (100%) · 65 mph: 52 of 52 (100%) · 70 mph: 12 of 12 (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 collision in both periods was 'The First Harmful Event was Not a Collision with a Motor Vehicle in Transport,' which decreased from 242 fatal crashes (67.8%) to 207 fatal crashes (65.7%). Angle collisions also decreased from 54 to 44 fatal crashes, while front-to-rear collisions increased from 21 to 29. Front-to-front collisions remained relatively stable, with 25 in the prior period and 26 in the current period.

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 most common vehicle body type involved in fatal crashes was '4-door sedan, hardtop,' decreasing from 149 in the prior period to 130 in the current period. 'Two Wheel Motorcycle' involvement increased from 53 to 62 fatal crashes, representing a notable rise in this high-fatality category. 'Light Pickup' involvement remained stable at 69 fatal crashes in both periods.

Vehicle Type

1
4-door sedan, hardtop130 (28.3%)
2
Light Pickup69 (15%)
3
Compact Utility (Utility Vehicle Categories "Small" and "Midsize")63 (13.7%)
4
Two Wheel Motorcycle (excluding motor scooters)62 (13.5%)
5
Large utility (ANSI D16.1 Utility Vehicle Categories and "Full Size" and "Large")26 (5.7%)
6
2-door sedan,hardtop,coupe16 (3.5%)
7
Station Wagon (excluding van and truck based)13 (2.8%)
8
5-door/4-door hatchback13 (2.8%)
9
Truck-tractor (Cab only, or with any number of trailing unit; any weight)11 (2.4%)

Showing top 9 of 30 reported. 21 additional (56 total) not shown: Unknown body type, Minivan (Chrysler Town and Country, Caravan, Grand Caravan, Voyager, Voyager, Honda-Odyssey, ...), Single-unit straight truck or Cab-Chassis (GVWR range 10,001 to 19,500 lbs.), Other or Unknown automobile type, Single-unit straight truck or Cab-Chassis (GVWR range 19,501 to 26,000 lbs.), 3-door/2-door hatchback, Recreational Off-Highway Vehicle, Large Van-Includes van-based buses (B150-B350, Sportsman, Royal Maxiwagon, Ram, Tradesman,...), Single-unit straight truck or Cab-Chassis (GVWR greater than 26,000 lbs.), Three-wheel Motorcycle (2 Rear Wheels), Utility Vehicle, Unknown body type, ATV/ATC [All-Terrain Cycle], Convertible(excludes sun-roof,t-bar), Farm equipment other than trucks, Medium/heavy Pickup (GVWR greater than 10,000 lbs.), Off-road Motorcycle, Other motored cycle type (mini-bikes, pocket motorcycles "pocket bikes"), Other vehicle type (includes go-cart, fork-lift, city street sweeper dunes/swamp buggy), Sedan/Hardtop, number of doors unknown, Transit Bus (City Bus), Unknown motored cycle type.

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

Rural vs Urban

Urban areas continued to account for the majority of fatal crashes, with 247 in the current period compared to 250 in the prior period. Rural fatal crashes saw a significant decrease, falling from 107 to 68 year-over-year. This indicates a notable reduction in fatal crashes occurring on rural trafficways.

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

Fatal crashes on 'Other Principal Arterial' roadways increased from 103 to 118, becoming the leading functional class for fatal crashes. Conversely, fatal crashes on 'Minor Arterial' roads decreased from 88 to 70, and on 'Interstate' roadways from 56 to 36. This suggests a shift in fatal crash concentration to other principal arterial roads.

Roadway Functional Class

1
Other Principal Arterial118 (37.6%)
2
Minor Arterial70 (22.3%)
3
Interstate36 (11.5%)
4
Major Collector34 (10.8%)
5
Other Freeways and Expressways26 (8.3%)
6
Local24 (7.6%)
7
Minor Collector6 (1.9%)

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 most roadways with fatal crashes, though their count decreased from 157 to 119. Fatal crashes on City or Municipal Highway Agency roads also decreased from 119 to 104. Fatal crashes on County Highway Agency roads decreased from 68 to 55, indicating a reduction across all reported ownership categories.

Roadway Ownership

1
State Highway Agency119 (42.8%)
2
City or Municipal Highway Agency104 (37.4%)
3
County Highway Agency55 (19.8%)

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

Person Type

Drivers remained the most common person type involved in fatal crashes, decreasing from 534 to 471. Pedestrian involvement also saw a decrease, from 123 to 110 persons. The number of passengers involved in fatal crashes decreased from 220 to 182, while bicyclists remained stable at 13 persons.

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 fatalities (K) decreased from 381 in the prior period to 334 in the current period. Persons sustaining serious injuries (A) decreased from 86 to 50, and those with minor injuries (B) remained relatively stable, decreasing slightly from 84 to 81. The number of persons with no reported injury (O) also decreased from 269 to 252.

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 number of persons using 'Shoulder and Lap Belt' in fatal crashes decreased from 472 to 411 year-over-year. Concurrently, the count of persons for whom 'None Used/Not Applicable' safety equipment was reported also decreased from 188 to 158. This indicates a general reduction in both belted and unbelted individuals in fatal crash data.

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 impact) remained the dominant point of impact in fatal crashes, decreasing from 269 in the prior period to 239 in the current period. Impacts at the '6 Clock Point' (rear impact) also decreased from 42 to 39, and 'Left' side impacts decreased from 30 to 24. This suggests a general reduction across common impact points.

Point of Impact

"Other" combines 13 smaller categories (38 records): Left-Front Side (7), Right-Back Side (6), 3 Clock Point (4), Left-Back Side (4), Reported as Unknown (3), 9 Clock Point (3), 5 Clock Point (3), 10 Clock Point (3), 1 Clock Point (1), 2 Clock Point (1), 11 Clock Point (1), Top (1), 7 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 decreased from 212 in the prior period to 186 in the current period. Fatal crashes involving two vehicles also saw a reduction, falling from 112 to 94. Crashes involving three vehicles remained relatively stable, with 23 in the prior period and 24 in the current period.

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: California
  • Total crash records analyzed: 315
  • Total persons involved: 788
  • Total vehicles involved: 474

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). "California 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/california/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

ThatCarHitMe.com · An Injuria.ai Company

SponsoredThatCarHitMe.com

Someone you love in this data? We’ll help you find out if you have a case.

Call our intake team. We connect you to a vetted California attorney who handles fatal-crash and wrongful death cases, and who will treat your family’s situation with care.

Always free for accident victims.