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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Yearly Traffic Safety Analysis

26 CRASHES IN
NORTH CHARLESTON, SOUTH CAROLINA
2023

All metrics benchmarked against2022

NORTH CHARLESTON experienced a notable increase in fatal crashes in 2023 compared to 2022. The number of fatal crashes rose by 18.18%, from 22 in 2022 to 26 in 2023, resulting in a 16.67% increase in total fatalities, from 24 to 28. The most significant shift was a 200% increase in fatal crashes involving DUI, rising from 3 to 9.

26

18.2%was 22

Total Crash Events

28

16.7%was 24

Persons Killed

14

75.0%was 8

Persons Injured

2

Hit-and-Run Crashes

Note: "Persons Killed" (28) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in fatal crash activity in NORTH CHARLESTON, with fatal crashes rising from 22 in 2022 to 26 in 2023, representing an 18.18% increase. Concurrently, the number of fatalities also increased by 16.67%, from 24 in 2022 to 28 in 2023. This suggests a worsening trend in traffic safety for the area.

2

Hit-and-Run Crashes — 2023

0.0% vs prior (2)

The number of fatal hit-and-run crashes remained stable at 2 in both 2022 and 2023. However, the hit-and-run rate decreased from 9.1% of fatal crashes in 2022 to 7.7% in 2023. This indicates that while the absolute number of such incidents did not change, they constitute a smaller proportion of the total fatal crashes.

Vulnerable Road User Casualties

10

Pedestrians Killed

Prior: 742.9%

18

Motorists Killed

Prior: 1612.5%

0

Pedestrians Injured

Prior: 1-100.0%

14

Motorists Injured

Prior: 7100.0%

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · 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 Thursday in 2022, with 7 fatal crashes, to Saturday in 2023, with 9 fatal crashes. While the peak hour remained at 3 fatal crashes, it shifted from 1 AM in 2022 to 8 PM in 2023. Fatal crashes on Saturdays saw a significant increase from 4 to 9, and Wednesdays increased from 1 to 3, while Thursdays decreased from 7 to 5.

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Road & Environmental Conditions

Fatal crashes occurring in clear weather conditions increased from 18 in 2022 to 22 in 2023, while crashes in rainy conditions decreased from 3 to 1. Fatal crashes in dark, lighted conditions increased from 5 to 7, and those in dark conditions with unknown lighting increased from 2 to 4. Road surface conditions data was not available for comparison.

Weather

Clear22 (84.6%)
22.2%prior 18
Cloudy3 (11.5%)
Rain1 (3.8%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight9 (34.6%)
0.0%prior 9
Dark - Lighted7 (26.9%)
40.0%prior 5
Dark - Not Lighted5 (19.2%)
0.0%prior 5
Dark - Unknown Lighting4 (15.4%)
Dusk1 (3.8%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (42 vehicles)

1
FORD7 (16.7%)
-36.4%prior 11
2
HONDA5 (11.9%)
3
CHEVROLET5 (11.9%)
4
DODGE5 (11.9%)
5
NISSAN/DATSUN3 (7.1%)
6
KIA2 (4.8%)
7
TOYOTA2 (4.8%)
8
INTERNATIONAL HARVESTER/NAVISTAR1 (2.4%)
9
KAWASAKI1 (2.4%)
10
LEXUS1 (2.4%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (62 persons with recorded sex)

Male45 (72.6%)
15.4%prior 39
Female17 (27.4%)
41.7%prior 12

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Fatal crashes occurring in 45 mph speed zones saw a substantial increase from 5 in 2022 to 13 in 2023. Conversely, fatal crashes in 40 mph zones decreased from 6 to 1. New fatal crashes were recorded in 25 mph zones in 2023 (2 fatal crashes), where none were reported in 2022, while 55 mph zones, which had 3 fatal crashes in 2022, had none in 2023.

Fatal crashes by zone: 25 mph: 2 of 2 (100%) · 30 mph: 1 of 1 (100%) · 35 mph: 3 of 3 (100%) · 40 mph: 1 of 1 (100%) · 45 mph: 13 of 13 (100%) · 60 mph: 3 of 3 (100%) · 65 mph: 1 of 1 (100%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · 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 increased from 12 fatal crashes in 2022 to 17 in 2023. Angle collisions decreased from 8 fatal crashes in 2022 to 4 in 2023. Additionally, front-to-front collisions, not present in 2022, accounted for 3 fatal crashes in 2023.

Manner of Collision

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash-level records

Vehicle Type

The most common vehicle body type involved in fatal crashes shifted slightly, with '4-door sedan, hardtop' decreasing from 14 in 2022 to 11 in 2023. Conversely, 'Large utility' vehicles saw an increase from 2 to 7 fatal crashes, and 'Light Pickup' increased from 6 to 7. Fatal crashes involving 'Two Wheel Motorcycle' decreased from 4 in 2022 to 2 in 2023.

Vehicle Type

1
4-door sedan, hardtop11 (26.2%)
2
Large utility (ANSI D16.1 Utility Vehicle Categories and "Full Size" and "Large")7 (16.7%)
3
Light Pickup7 (16.7%)
4
Minivan (Chrysler Town and Country, Caravan, Grand Caravan, Voyager, Voyager, Honda-Odyssey, ...)4 (9.5%)
5
2-door sedan,hardtop,coupe3 (7.1%)
6
Compact Utility (Utility Vehicle Categories "Small" and "Midsize")2 (4.8%)
7
Station Wagon (excluding van and truck based)2 (4.8%)
8
Truck-tractor (Cab only, or with any number of trailing unit; any weight)2 (4.8%)
9
Two Wheel Motorcycle (excluding motor scooters)2 (4.8%)

Showing top 9 of 11 reported. 2 additional (2 total) not shown: 3-door/2-door hatchback, Unknown body type.

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Vehicle unit records

Roadway Functional Class

Fatal crashes on 'Other Principal Arterial' roadways increased from 11 in 2022 to 14 in 2023, remaining the most common functional class for fatal crashes. Fatal crashes on 'Interstate' roadways decreased from 6 to 4. There was an increase in fatal crashes on 'Local' roadways from 1 to 3, and on 'Major Collector' roadways from 2 to 3.

Roadway Functional Class

1
Other Principal Arterial14 (53.8%)
2
Interstate4 (15.4%)
3
Local3 (11.5%)
4
Major Collector3 (11.5%)
5
Minor Arterial1 (3.8%)
6
Minor Collector1 (3.8%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash-level records

Roadway Ownership

State Highway Agencies continued to own the roadways with the most fatal crashes, increasing slightly from 21 in 2022 to 22 in 2023. Fatal crashes on roadways owned by County Highway Agencies saw a significant increase, rising from 1 in 2022 to 4 in 2023. This indicates a shift in the distribution of fatal crashes across different ownership types.

Roadway Ownership

1
State Highway Agency22 (84.6%)
2
County Highway Agency4 (15.4%)

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash-level records

Person Type

The number of drivers involved in fatal crashes increased from 38 in 2022 to 42 in 2023, remaining the dominant person type. Pedestrians involved in fatal crashes increased from 8 to 10, and passengers increased from 6 to 11. Bicyclists, who accounted for 1 person in 2022, were not involved in any fatal crashes in 2023.

Person Type

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash-level records

Person Injury Severity

The number of fatalities (K) increased from 24 in 2022 to 28 in 2023. Persons with no reported injuries (O) remained stable at 21 in both periods. There was a notable increase in possible injuries (C) from 2 in 2022 to 11 in 2023, while serious injuries (A) decreased from 3 to 2 and minor injuries (B) decreased from 3 to 1.

Person Injury Severity

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Crash-level records

Occupant Safety Equipment

The use of 'Shoulder and Lap Belt Used' in fatal crashes increased from 17 persons in 2022 to 28 in 2023. Conversely, the number of persons reported with 'None Used/Not Applicable' safety equipment decreased from 10 to 7. The count of 'Reported as Unknown' safety equipment use slightly increased from 17 to 18 persons.

Occupant Safety Equipment

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Point of Impact

The '12 Clock Point' (front impact) remained the most common point of impact, increasing from 22 instances in 2022 to 30 in 2023. Impacts at the '9 Clock Point' decreased from 6 to 4. Impacts at the '3 Clock Point' remained consistent at 5 instances in both periods, while '6 Clock Point' impacts decreased from 3 to 1.

Point of Impact

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · Vehicle unit records

Vehicles Per Crash

Single-vehicle fatal crashes increased from 10 in 2022 to 14 in 2023, making them the most frequent type. Two-vehicle fatal crashes slightly decreased from 9 to 8. Three-vehicle fatal crashes increased from 2 to 3, while five-vehicle fatal crashes remained stable at 1 in both periods.

Vehicles Per Crash

Source: NHTSA FARS (Fatal Crashes) · Federal fatal-crash census · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: August 5, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: North Charleston, South Carolina
  • Total crash records analyzed: 26
  • Total persons involved: 63
  • Total vehicles involved: 42

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). "North Charleston, South Carolina Crash Intelligence Report: 2023." Published August 5, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: NHTSA FARS (Fatal Crashes), NHTSA FARS Open Data. Available at: https://thatcarhitme.com/crash-data/south-carolina/fatal/north-charleston/2023-annual-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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