Yearly Traffic Safety Analysis

293 CRASHES IN
ASHLAND, OH
2023

All metrics benchmarked against2022

Ashland experienced a decrease in total crashes, falling from 324 in the prior year to 293 in the current year, representing a 9.6% reduction. A significant positive shift was observed with total fatalities decreasing from 2 to 0, marking a complete elimination of crash-related deaths year-over-year. Overall, the data indicates a general improvement in traffic safety metrics for the period.

293

-9.6%was 324

Total Crash Events

0

-100.0%was 2

Persons Killed

82

-26.1%was 111

Persons Injured

31

-13.9%was 36

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Ashland shows a decline in traffic incidents, with total crashes decreasing from 324 to 293, a reduction of 31 crashes. This positive trend is further supported by a decrease in total injuries from 111 to 82, and a notable elimination of crash fatalities, which dropped from 2 to 0.

31

Hit-and-Run Crashes — 2023

-13.9% vs prior (36)

Hit-and-run crashes decreased from 36 incidents in the prior year to 31 in the current year. Consequently, the hit-and-run rate also saw a slight reduction, moving from 11.1% of total crashes to 10.6%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 2-100.0%

3

Pedestrians Injured

Prior: 4-25.0%

79

Motorists Injured

Prior: 107-26.2%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 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 crashes shifted from Friday in the prior year (70 crashes) to Thursday in the current year (53 crashes), with Friday crashes seeing a substantial decrease of 25 incidents. The peak crash hour remained consistent at 4 PM across both periods, with 33 crashes in the current year compared to 32 in the prior year, showing little change in this specific temporal pattern.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

A significant improvement in crash severity was observed, with total fatalities decreasing from 2 in the prior year to 0 in the current year. Serious injuries (Severity A) also saw a reduction, dropping from 8 (2.5% of crashes) to 5 (1.7% of crashes). While minor injuries (Severity B) slightly increased from 37 to 39, possible injuries (Severity C) decreased from 29 to 22.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes1.7%
-37.5%prior 8
Minor Injury39minor injury crashes13.3%
5.4%prior 37
Possible Injury22possible injury crashes7.5%
-24.1%prior 29
No Injury227no injury crashes77.5%
-8.8%prior 249

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 207 to 191, and those in snowy conditions dropped from 18 to 9. Conversely, crashes during rainy conditions saw a slight increase from 22 to 29. While most lighting and road surface conditions showed fewer crashes in line with the overall reduction, crashes on dark, unlighted roadways increased from 17 to 21.

Weather

Clear191 (65.2%)
-7.7%prior 207
Cloudy60 (20.5%)
-13.0%prior 69
Rain29 (9.9%)
31.8%prior 22
Snow9 (3.1%)
-50.0%prior 18
Other/Unknown3 (1.0%)
-50.0%prior 6
Fog; Smog; Smoke1 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight202 (68.9%)
-11.4%prior 228
Dark - Lighted Roadway42 (14.3%)
-14.3%prior 49
Dark - Roadway Not Lighted21 (7.2%)
23.5%prior 17
Dawn/Dusk19 (6.5%)
-5.0%prior 20
Dark - Unknown Roadway Lighting5 (1.7%)
0.0%prior 5
Other/Unknown4 (1.4%)
-20.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry237 (80.9%)
-5.2%prior 250
Wet48 (16.4%)
-7.7%prior 52
Snow6 (2.0%)
-60.0%prior 15
Ice2 (0.7%)
-66.7%prior 6

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 600 to 565 year-over-year. Notably, crashes involving Semi-Tractors decreased significantly from 19 to 6, and incidents involving persons aged 65 and older dropped from 144 to 105. Toyota and Jeep vehicles saw a decrease in involvement, while Chevrolet, Ford, and Honda vehicles saw slight increases in crash counts.

Top Vehicle Makes (565 vehicles)

1
CHEVROLET114 (20.2%)
8.6%prior 105
2
FORD111 (19.6%)
0.9%prior 110
3
HONDA46 (8.1%)
15.0%prior 40
4
DODGE39 (6.9%)
8.3%prior 36
5
TOYOTA34 (6%)
-30.6%prior 49
6
JEEP30 (5.3%)
-26.8%prior 41
7
KIA28 (5%)
-3.4%prior 29
8
GMC17 (3%)
-15.0%prior 20
9
HYUNDAI17 (3%)
30.8%prior 13
10
CHRYSLER17 (3%)
6.3%prior 16

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (705 persons with recorded sex)

Male360 (51.1%)
-9.1%prior 396
Female345 (48.9%)
-11.1%prior 388

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv 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: Csv 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: July 6, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: Ashland, OH
  • Total crash records analyzed: 293
  • Total persons involved: 724
  • Total vehicles involved: 565

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). "Ashland, OH Crash Intelligence Report: 2023." Published July 6, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/ashland/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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Ashland, OH Crash Report — 2023 | ThatCarHitMe.com