Monthly Traffic Safety Analysis

8 CRASHES IN
CLINTON, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

CLINTON, MA experienced a significant increase in total crashes in March 2022 compared to March 2021, rising from 3 crashes to 8 crashes, a 166.67% increase. This period also saw the emergence of DUI-related crashes, with 2 such incidents reported in March 2022 compared to none in the prior year. Total injuries doubled from 1 to 2 year-over-year, while fatalities remained at 0 in both periods.

8

166.7%was 3

Total Crash Events

0

Persons Killed

2

100.0%was 1

Persons Injured

0

Fatal Crash Events

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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in CLINTON, MA showed a rising trend year-over-year. Total crashes increased by 166.67%, from 3 crashes in March 2021 to 8 crashes in March 2022. Concurrently, total injuries increased by 100%, from 1 injury in March 2021 to 2 injuries in March 2022.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 1100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. The peak day for crashes changed from Friday in March 2021 (1 crash) to Thursday in March 2022 (2 crashes). The peak hour for crashes also shifted, moving from 4 PM in March 2021 (2 crashes) to 7 PM in March 2022 (2 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both March 2021 and March 2022. While the total number of injuries increased from 1 to 2, the proportion of crashes resulting in any injury decreased from 33.3% in March 2021 (1 injury crash out of 3 total) to 25% in March 2022 (2 injury crashes out of 8 total).

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes12.5%
Possible Injury1possible injury crashes12.5%
0.0%prior 1
No Injury6no injury crashes75%
200.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Contributing factors saw shifts and new entries year-over-year. 'Inattention' increased from 1 crash in March 2021 to 2 crashes in March 2022, while 'No improper driving' remained constant at 1 crash in both periods. Factors such as 'Disregarded traffic signs, signals, road markings' and 'Physical impairment' each contributed to 2 crashes in March 2022, having not been present in the top factors for March 2021.

Officer-Reported Primary Contributing Cause

Disregarded traffic signs, signals, road markings2 (25%)
Inattention2 (25%)
Physical impairment2 (25%)
No improper driving1 (12.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In terms of lighting conditions, crashes occurring during 'Daylight' increased from 2 in March 2021 to 4 in March 2022, while 'Dark - lighted roadway' crashes remained at 1 in both periods. 'Dusk' crashes, accounting for 3 incidents in March 2022, were not observed in March 2021. Data for weather and road surface conditions were not consistently available for comparison across both periods.

Weather

Clear/Clear5 (62.5%)
Clear/Cloudy1 (12.5%)
Clear/Unknown1 (12.5%)
Snow/Sleet, hail (freezing rain or drizzle)1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight4 (50.0%)
Dusk3 (37.5%)
Dark - lighted roadway1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry7 (87.5%)
Ice1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (18 vehicles)

1
NISSAN2 (11.1%)
2
CHEVY SILVER1 (5.6%)
3
FORD1 (5.6%)
4
FORD ESCAPE1 (5.6%)
5
GMC SIERRA1 (5.6%)
6
HONDA1 (5.6%)
7
HONDA CIVIC1 (5.6%)
8
HONDA RIDGLELIN1 (5.6%)
9
HYUNDI1 (5.6%)
10
HYUN ELANTRA1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (20 persons with recorded sex)

Male11 (55.0%)
120.0%prior 5
Female9 (45.0%)
800.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

All crashes in both March 2021 and March 2022 occurred within 30 mph speed zones. The number of crashes in this speed zone increased from 3 in March 2021 to 8 in March 2022. Fatal crashes remained at 0 in 30 mph zones for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: CLINTON, MA
  • Total crash records analyzed: 8
  • Total persons involved: 22
  • Total vehicles involved: 18

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). "CLINTON, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/clinton/march-2022-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

Clinton, MA Crash Report — March 2022 | ThatCarHitMe.com