ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ASHLAND, OH · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/ohio/ashland/2022-annual-report
Yearly Traffic Safety Analysis
324 CRASHES IN
ASHLAND, OH
2022
Ashland experienced an increase in overall crash activity from 2021 to 2022. Total crashes rose by 10.20%, from 294 to 324. The most notable shift was the increase in total fatalities, which went from 0 in 2021 to 2 in 2022.
324
▲ 10.2%was 294
Total Crash Events
2
Persons Killed
111
▲ 26.1%was 88
Persons Injured
36
▲ 24.1%was 29
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Ashland show an increase from 2021 to 2022. Total crashes rose by 10.20%, from 294 to 324. Concurrently, total injuries increased by 26.14%, from 88 to 111, and total fatalities increased from 0 to 2.
36
Hit-and-Run Crashes — 2022
▲ 24.1% vs prior (29)
Hit-and-run crashes increased from 29 in 2021 to 36 in 2022. The hit-and-run rate also rose from 9.9% of all crashes in 2021 to 11.1% in 2022, indicating an upward trend in both the count and proportion of these incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
4
Pedestrians Injured
107
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday, increasing from 57 crashes in 2021 to 70 crashes in 2022. Similarly, the peak hour remained 4 PM, with crashes rising from 28 to 32 during this time. While crashes on Monday and Saturday decreased, incidents on Tuesday, Wednesday, Thursday, and Sunday all saw increases year-over-year.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 0 in 2021 to 1 in 2022, resulting in a fatal crash rate of 0.31% in 2022 compared to 0% in the prior year. Serious injury crashes decreased from 11 (3.7% of total crashes) in 2021 to 8 (2.5% of total crashes) in 2022. Conversely, possible injury crashes increased from 17 (5.8% of total crashes) to 29 (9% of total crashes).
Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 185 in 2021 to 207 in 2022, while crashes in cloudy and rainy conditions slightly decreased. Crashes in snowy conditions more than doubled, rising from 8 in 2021 to 18 in 2022. This corresponds with an increase in crashes on snowy road surfaces from 6 to 15, and on icy surfaces from 2 to 6.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The involvement of Sport Utility Vehicles (SUVs) in crashes increased by 35.1%, from 131 in 2021 to 177 in 2022, and Semi-Tractors increased by 72.7% from 11 to 19. Ford became the most frequently involved vehicle make, with 110 incidents in 2022, surpassing Chevrolet which had 105 incidents. The 65+ age group experienced the largest increase in persons involved in crashes, rising from 111 in 2021 to 144 in 2022, while the 21-25 age group saw a decrease from 84 to 74.
Top Vehicle Makes (600 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
33 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (784 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: July 6, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: Ashland, OH
- Total crash records analyzed: 324
- Total persons involved: 806
- Total vehicles involved: 600
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: 2022." Published July 6, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/ashland/2022-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Ohio Crash Data (ODOT TIMS) · Csv
Period: 2022-01-01 – 2022-12-31
Generated: July 6, 2026 · All rights reserved