Yearly Traffic Safety Analysis

469 CRASHES IN
SOMERSET, MA
2023

All metrics benchmarked against2022

In 2023, Somerset recorded 469 total traffic crashes, an increase of 9.8% from the 427 crashes reported in 2022. The most significant year-over-year change was the increase in traffic fatalities, which rose from zero in 2022 to six in 2023.

469

9.8%was 427

Total Crash Events

6

Persons Killed

160

3.9%was 154

Persons Injured

28

180.0%was 10

Hit-and-Run Crashes

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 10 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Somerset show an increase from 2022 to 2023. Total crashes rose by 9.8%, from 427 to 469. While total injuries saw a modest increase of 3.9% from 154 to 160, the number of fatalities increased from zero to six.

28

Hit-and-Run Crashes — 2023

180.0% vs prior (10)

Hit-and-run incidents increased substantially from 2022 to 2023. The number of hit-and-run crashes rose from 10 to 28, representing a 180% increase. The hit-and-run rate, as a percentage of total crashes, also trended upwards, increasing from 2.3% in 2022 to 6.0% in 2023.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

5

Motorists Killed

Prior: 0%

3

Pedestrians Injured

Prior: 250.0%

3

Cyclists Injured

Prior: 250.0%

154

Motorists Injured

Prior: 1502.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 the two periods. In 2023, the peak day for crashes was Friday with 85 incidents, a change from Saturday (73 incidents) in 2022. The peak hour also shifted earlier, from 5 p.m. in 2022 (42 crashes) to 2 p.m. in 2023 (43 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased significantly from 2022 to 2023. The number of fatal crashes rose from zero to three, and serious injury crashes increased from four to 11. Consequently, the share of crashes resulting in serious injury grew from 0.9% in 2022 to 2.3% in 2023. The proportion of crashes with minor or no injuries remained relatively stable, accounting for 89.4% of all crashes in 2023 compared to 89.9% in 2022.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 6 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
Serious Injury11serious injury crashes2.3%
175.0%prior 4
Minor Injury82minor injury crashes17.5%
7.9%prior 76
Possible Injury26possible injury crashes5.5%
0.0%prior 26
No Injury337no injury crashes71.9%
9.4%prior 308

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted between 2022 and 2023. 'Inattention' became the most cited factor in 2023 with 88 crashes, an 18.9% increase in count from 74 in 2022. Crashes attributed to 'Failed to yield right of way' also saw a notable increase in count, rising from 66 to 87. Conversely, crashes with 'No improper driving' cited decreased in count from 83 to 74, dropping from the top-ranked factor in 2022 to third in 2023.

Officer-Reported Primary Contributing Cause

Inattention88 (18.8%)18.9%prior 74
Failed to yield right of way87 (18.6%)31.8%prior 66
No improper driving74 (15.8%)-10.8%prior 83
Followed too closely69 (14.7%)13.1%prior 61
Failure to keep in proper lane or running off road30 (6.4%)30.4%prior 23
Other improper action14 (3%)0.0%prior 14
Disregarded traffic signs, signals, road markings14 (3%)180.0%prior 5
Driving too fast for conditions11 (2.3%)-35.3%prior 17
Distracted9 (1.9%)50.0%prior 6
Visibility obstructed8 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely consistent year-over-year. In both 2022 and 2023, the majority of crashes occurred in daylight (69.3% and 73.3% respectively) and clear weather (74.5% and 78.0% respectively). The proportion of crashes on dry road surfaces increased from 76.6% in 2022 to 83.6% in 2023, while the share of crashes on wet surfaces decreased from 17.1% to 14.1%.

Weather

Clear366 (78.9%)
15.1%prior 318
Rain35 (7.5%)
-7.9%prior 38
Cloudy30 (6.5%)
15.4%prior 26
Cloudy/Rain13 (2.8%)
-7.1%prior 14
Clear/Other7 (1.5%)
Rain/Other4 (0.9%)
Rain/Severe crosswinds2 (0.4%)
Snow2 (0.4%)
-87.5%prior 16
Rain/Cloudy1 (0.2%)
Cloudy/Fog, smog, smoke1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight344 (74.0%)
16.2%prior 296
Dark - lighted roadway95 (20.4%)
1.1%prior 94
Dark - roadway not lighted11 (2.4%)
-35.3%prior 17
Dawn8 (1.7%)
33.3%prior 6
Dusk5 (1.1%)
-44.4%prior 9
Dark - unknown roadway lighting1 (0.2%)
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry392 (84.3%)
19.9%prior 327
Wet66 (14.2%)
-9.6%prior 73
Ice2 (0.4%)
Sand, mud, dirt, oil, gravel2 (0.4%)
Water (standing, moving)2 (0.4%)
Slush1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The characteristics of vehicles and persons involved in crashes were similar across both years. The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both 2022 and 2023. Similarly, the age distribution of persons involved showed a consistent pattern, with the 65+ age group representing the largest cohort in both periods, accounting for 139 individuals in 2022 and 158 in 2023.

Top Vehicle Makes (866 vehicles)

1
TOYOTA144 (16.6%)
5.9%prior 136
2
HONDA97 (11.2%)
14.1%prior 85
3
FORD72 (8.3%)
10.8%prior 65
4
NISSAN61 (7%)
17.3%prior 52
5
CHEVROLET56 (6.5%)
-9.7%prior 62
6
JEEP47 (5.4%)
56.7%prior 30
7
HYUNDAI43 (5%)
0.0%prior 43
8
KIA35 (4%)
-2.8%prior 36
9
DODGE28 (3.2%)
55.6%prior 18
10
SUBARU27 (3.1%)
-10.0%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (953 persons with recorded sex)

Male528 (55.4%)
14.5%prior 461
Female425 (44.6%)
9.5%prior 388

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones were most frequent in both periods, with 189 incidents in 2022 and 198 in 2023. There was a notable increase in crashes within 40 mph zones, which rose from 66 in 2022 to 90 in 2023. While no fatal crashes were recorded in 2022, the three fatal crashes in 2023 occurred in zones with posted speed limits of 20 mph, 40 mph, and 55 mph.

Fatal crashes by zone: 20 mph: 1 of 9 (11.111%) · 40 mph: 1 of 90 (1.111%) · 55 mph: 1 of 21 (4.762%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: SOMERSET, MA
  • Total crash records analyzed: 469
  • Total persons involved: 1,069
  • Total vehicles involved: 866

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/somerset/2023-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

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Somerset, MA Crash Report — 2023 | ThatCarHitMe.com