ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SHARON, MA · 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/massachusetts/sharon/2022-annual-report
Yearly Traffic Safety Analysis
392 CRASHES IN
SHARON, MA
2022
In 2022, Sharon recorded 392 total traffic crashes, a 21.7% increase from the 322 crashes documented in 2021. This rise in collisions was accompanied by a significant year-over-year change in crash severity, with total fatalities increasing from one in 2021 to five in 2022.
392
▲ 21.7%was 322
Total Crash Events
5
▲ 400.0%was 1
Persons Killed
177
▲ 22.1%was 145
Persons Injured
19
▲ 850.0%was 2
Hit-and-Run Crashes
Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 17 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Sharon showed a clear upward trend from 2021 to 2022. Total collisions increased by 21.7%, from 322 to 392. This increase was mirrored by a 22.1% rise in the number of people injured, from 145 to 177, and a 400% increase in fatalities, from one to five.
19
Hit-and-Run Crashes — 2022
▲ 850.0% vs prior (2)
Hit-and-run incidents increased dramatically between the two periods. The number of hit-and-run crashes surged from two in 2021 to 19 in 2022, an 850% increase. Consequently, the hit-and-run rate as a percentage of total crashes rose from 0.6% to 4.8%, marking a significant upward trend.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
2
Pedestrians Injured
1
Cyclists Injured
172
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly 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 temporal patterns of crashes shifted between 2021 and 2022. The peak day for crashes moved from Wednesday (53 crashes) in 2021 to Friday (66 crashes) in 2022. Similarly, the peak hour for collisions shifted from the 8 a.m. morning commute hour in 2021 (27 crashes) to the 3 p.m. afternoon hour in 2022 (32 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased notably in 2022, with the number of fatal crashes rising from one to five, causing the fatal crash rate to more than quadruple from 0.31% to 1.28%. While the proportion of serious injury crashes decreased from 3.1% to 1.3% of all crashes, the share of minor injury crashes grew from 15.2% in 2021 to 18.1% in 2022. The proportion of crashes resulting in no injury remained stable at 64% for both years.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with "No improper driving" cited in 94 crashes in both 2021 and 2022. However, crashes attributed to "Inattention" saw a 40% increase in count, rising from 35 to 49 incidents, to become the second-leading factor in 2022. Crashes where a driver was "Distracted" more than doubled, increasing by 157% from 7 incidents in 2021 to 18 in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred in favorable conditions, with over 64% happening in daylight and on dry roads. In 2022, 74.2% of crashes were on dry roads, compared to 77.3% in 2021. One notable shift was the emergence of icy road conditions as a factor, accounting for 19 crashes in 2022 whereas no crashes were recorded for this condition in 2021.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Honda and Toyota leading in both years; Honda (106 vehicles) surpassed Toyota (104 vehicles) for the top spot in 2022 after being second in 2021. Regarding the demographics of people involved, the proportion of individuals aged 16-20 increased from 11.5% of the total in 2021 to 13.1% in 2022. Conversely, the share of individuals in the 45-54 age group decreased from 14.1% to 10.2% over the same period.
Top Vehicle Makes (669 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
36 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (778 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in higher speed zones saw an increase in 2022. Collisions in 65 mph zones rose from 80 in 2021 to 101 in 2022, while crashes in 25 mph zones also increased from 47 to 61. In 2022, five fatalities resulted from crashes that occurred in 35 mph, 40 mph, and 65 mph zones. This contrasts with 2021, which had a single fatal crash that occurred in a 40 mph zone.
Fatal crashes by zone: 35 mph: 2 of 106 (1.887%) · 40 mph: 1 of 21 (4.762%) · 65 mph: 2 of 101 (1.98%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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: Arcgis_yearly 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: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: SHARON, MA
- Total crash records analyzed: 392
- Total persons involved: 850
- Total vehicles involved: 669
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). "SHARON, MA Crash Intelligence Report: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sharon/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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved