Monthly Traffic Safety Analysis

39 CRASHES IN
EASTON, MA
FEBRUARY 2022

All metrics benchmarked againstFebruary 2021

In February 2022, Easton experienced a notable decrease in overall crash activity compared to February 2021, with total crashes falling from 50 to 39, representing a 22% reduction. The most significant year-over-year shift was in total injuries, which decreased by 46.15%, from 26 to 14 persons injured.

39

-22.0%was 50

Total Crash Events

0

Persons Killed

14

-46.2%was 26

Persons Injured

1

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Easton showed a decline year-over-year, with total crashes decreasing by 22% from 50 in February 2021 to 39 in February 2022. This reduction was accompanied by a substantial 46.15% decrease in total injuries, from 26 to 14, indicating a positive trend in traffic safety outcomes.

1

Hit-and-Run Crashes — February 2022

2.6% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

14

Motorists Injured

Prior: 26-46.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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 the two periods; the peak day for crashes moved from Tuesday with 17 crashes in February 2021 to Thursday with 8 crashes in February 2022. Similarly, the peak hour for crashes changed from 3 PM with 8 crashes in February 2021 to 12 PM with 6 crashes in February 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities reported in either February 2021 or February 2022. While the total number of injury crashes (categorized as serious, minor, or possible) remained constant at 11 in both periods, the proportion of crashes resulting in injury increased from 22% in February 2021 to 28.2% in February 2022. The number of serious injury crashes decreased from 2 to 1, while minor injury crashes increased from 5 to 6, and possible injury crashes remained at 4.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.6%
-50.0%prior 2
Minor Injury6minor injury crashes15.4%
20.0%prior 5
Possible Injury4possible injury crashes10.3%
0.0%prior 4
No Injury26no injury crashes66.7%
-31.6%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors shifted year-over-year, with 'Failed to yield right of way' increasing from 4 crashes in February 2021 to 10 crashes in February 2022. Conversely, 'No improper driving' decreased from 15 crashes to 8 crashes, and 'Driving too fast for conditions' saw a significant drop from 7 crashes to 2 crashes. 'Followed too closely' increased in count from 1 to 4 crashes, while 'Disregarded traffic signs, signals, road markings' decreased from 6 to 2 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way10 (25.6%)
No improper driving8 (20.5%)-46.7%prior 15
Followed too closely4 (10.3%)
Disregarded traffic signs, signals, road markings2 (5.1%)-66.7%prior 6
Driving too fast for conditions2 (5.1%)-71.4%prior 7
Over-correcting/over-steering2 (5.1%)
Fatigued/asleep1 (2.6%)
Operating defective equipment1 (2.6%)
Failure to keep in proper lane or running off road1 (2.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift towards fewer crashes occurring in adverse weather and road surface conditions in February 2022 compared to February 2021. The proportion of crashes in non-clear/cloudy weather decreased from 44% to 15.4%, and crashes on non-dry road surfaces fell from 62% to 35.9%. Crashes in dark or low light conditions also decreased from 40% in February 2021 to 30.8% in February 2022.

Weather

Clear27 (69.2%)
35.0%prior 20
Cloudy6 (15.4%)
0.0%prior 6
Rain2 (5.1%)
Snow2 (5.1%)
-83.3%prior 12
Sleet, hail (freezing rain or drizzle)1 (2.6%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash

Lighting

Daylight27 (69.2%)
-10.0%prior 30
Dark - lighted roadway9 (23.1%)
-30.8%prior 13
Dark - roadway not lighted1 (2.6%)
Dawn1 (2.6%)
Dusk1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field

Road Surface

Dry25 (64.1%)
31.6%prior 19
Wet7 (17.9%)
-12.5%prior 8
Ice3 (7.7%)
-62.5%prior 8
Snow3 (7.7%)
-80.0%prior 15
Other1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field

Vehicles & Demographics

TOYOTA remained the most frequently involved vehicle make in both periods, although its count decreased from 17 in February 2021 to 10 in February 2022. The 26-34 age group remained the largest demographic involved in crashes, with 17 persons in both periods, while the 55-64 age group saw a decrease from 22 to 12 persons involved. The number of males involved in crashes decreased from 55 to 40, and females decreased from 45 to 35.

Top Vehicle Makes (67 vehicles)

1
TOYOTA10 (14.9%)
-41.2%prior 17
2
NISSAN7 (10.4%)
40.0%prior 5
3
FORD6 (9%)
-57.1%prior 14
4
CHEVROLET6 (9%)
5
SUBARU5 (7.5%)
6
ACURA4 (6%)
7
LEXUS4 (6%)
8
HONDA4 (6%)
-50.0%prior 8
9
HYUNDAI4 (6%)
10
MAZDA3 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records

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

Sex Distribution (75 persons with recorded sex)

Male40 (53.3%)
-27.3%prior 55
Female35 (46.7%)
-22.2%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 40 mph speed zones, which were the most frequent, decreased from 24 in February 2021 to 17 in February 2022. Crashes in 35 mph zones also decreased from 10 to 7, while 30 mph zones remained constant with 9 crashes in both periods. There were no fatal crashes recorded in any speed zone during either the current or prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-02-01 through 2022-02-28 (28 days)
  • Geographic scope: EASTON, MA
  • Total crash records analyzed: 39
  • Total persons involved: 80
  • Total vehicles involved: 67

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). "EASTON, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/easton/february-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

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Easton, MA Crash Report — February 2022 | ThatCarHitMe.com