Monthly Traffic Safety Analysis

31 CRASHES IN
SOMERSET, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

Total crashes in Somerset decreased by 6.1%, from 33 in March 2022 to 31 in March 2023. Despite this reduction, total injuries saw a slight increase of 6.3%, rising from 16 to 17. The most notable shift was in contributing factors, with crashes attributed to 'Failed to yield right of way' increasing by 233.3% in count, from 3 to 10.

31

-6.1%was 33

Total Crash Events

0

Persons Killed

17

6.3%was 16

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for total crashes in Somerset was a slight decrease year-over-year, falling from 33 crashes in March 2022 to 31 crashes in March 2023, representing a 6.1% reduction. However, total injuries increased by 6.3%, from 16 to 17, while fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

16

Motorists Injured

Prior: 156.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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 Wednesday in both periods, with 10 crashes in March 2022 and 11 crashes in March 2023. The peak hour for crashes shifted from 4 p.m. in March 2022 to 6 p.m. in March 2023, with both hours recording 4 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both March 2022 and March 2023. Total injuries increased from 16 to 17, a 6.3% rise. Serious injury crashes remained stable at 1 crash in both periods, while minor injury crashes increased from 5 (15.2% share) to 6 (19.4% share). Possible injury crashes decreased from 4 (12.1% share) to 2 (6.5% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.2%
0.0%prior 1
Minor Injury6minor injury crashes19.4%
20.0%prior 5
Possible Injury2possible injury crashes6.5%
-50.0%prior 4
No Injury21no injury crashes67.7%
-8.7%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Failed to yield right of way' saw a significant increase, rising from 3 crashes in March 2022 to 10 crashes in March 2023, a 233.3% increase in count. Conversely, 'Inattention' decreased by 57.1% in count, from 7 crashes to 3 crashes, and 'Followed too closely' decreased by 50% in count, from 6 crashes to 3 crashes. 'Failed to yield right of way' became the most frequent factor in March 2023 (32.3% share), moving from fourth place in March 2022 (9.1% share).

Officer-Reported Primary Contributing Cause

Failed to yield right of way10 (32.3%)
No improper driving3 (9.7%)-40.0%prior 5
Followed too closely3 (9.7%)-50.0%prior 6
Inattention3 (9.7%)-57.1%prior 7
Failure to keep in proper lane or running off road2 (6.5%)
Made an improper turn2 (6.5%)
Disregarded traffic signs, signals, road markings1 (3.2%)
Driving too fast for conditions1 (3.2%)
Other improper action1 (3.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions remained the most frequent, with 25 in March 2022 and 26 in March 2023. Crashes during daylight hours decreased from 25 to 20, while those in 'Dark - lighted roadway' conditions increased from 5 to 8. Dry road surface crashes decreased from 29 to 27, and wet road crashes increased from 3 to 4, while snow conditions were reported in 1 crash in March 2022 but not in March 2023.

Weather

Clear26 (83.9%)
4.0%prior 25
Cloudy2 (6.5%)
Clear/Other1 (3.2%)
Cloudy/Rain1 (3.2%)
Rain1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight20 (64.5%)
-20.0%prior 25
Dark - lighted roadway8 (25.8%)
60.0%prior 5
Dark - roadway not lighted2 (6.5%)
Dusk1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry27 (87.1%)
-6.9%prior 29
Wet4 (12.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

TOYOTA remained the most involved vehicle make, increasing from 11 vehicles in March 2022 to 12 in March 2023. NISSAN also saw an increase from 6 to 7 vehicles, while HYUNDAI decreased from 6 to 4 vehicles. Significant shifts were observed in the age distribution of persons involved in crashes, with the 0-15 age group increasing from 1 to 8 persons, and the 21-25 age group rising from 3 to 13 persons.

Top Vehicle Makes (55 vehicles)

1
TOYOTA12 (21.8%)
9.1%prior 11
2
NISSAN7 (12.7%)
16.7%prior 6
3
HYUNDAI4 (7.3%)
-33.3%prior 6
4
FORD4 (7.3%)
5
HONDA4 (7.3%)
-20.0%prior 5
6
KIA3 (5.5%)
7
DODGE3 (5.5%)
8
CHEVROLET3 (5.5%)
9
JEEP2 (3.6%)
10
TRIU1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

Sex Distribution (69 persons with recorded sex)

Male38 (55.1%)
18.8%prior 32
Female31 (44.9%)
19.2%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone remained constant at 14 crashes in both periods, making it the most frequent speed zone for crashes. Crashes in the 25 mph zone increased from 1 to 2, and in the 35 mph zone from 2 to 4. Notably, crashes in the 5 mph, 20 mph, and 65 mph zones, which occurred in March 2022, were not reported in March 2023, while a crash in a 10 mph zone appeared in March 2023. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: SOMERSET, MA
  • Total crash records analyzed: 31
  • Total persons involved: 71
  • Total vehicles involved: 55

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). "SOMERSET, MA Crash Intelligence Report: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/somerset/march-2023-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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Somerset, MA Crash Report — March 2023 | ThatCarHitMe.com