Monthly Traffic Safety Analysis

30 CRASHES IN
SOMERSET, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Somerset experienced 30 total crashes, a decrease of 11.76% compared to the 34 crashes reported in September 2023. A notable year-over-year shift is the absence of fatalities in the current period, down from 2 fatalities in the prior year.

30

-11.8%was 34

Total Crash Events

0

-100.0%was 2

Persons Killed

7

-12.5%was 8

Persons Injured

3

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 · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Somerset saw a downward trend in September 2024 compared to the same month in the prior year. Total crashes decreased by 11.76%, from 34 to 30, while total injuries also saw a slight reduction from 8 to 7. Critically, fatalities dropped from 2 in September 2023 to 0 in September 2024.

3

Hit-and-Run Crashes — September 2024

10.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 2-100.0%

1

Cyclists Injured

Prior: 0%

6

Motorists Injured

Prior: 8-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 year-over-year. In September 2023, the peak day for crashes was Friday with 8 incidents, and the peak hour was 8 AM with 5 incidents. However, in September 2024, the peak day moved to Tuesday with 6 crashes, and the peak hour shifted to 7 PM, recording 3 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes improved significantly, with no fatal crashes or fatalities reported in September 2024, compared to 1 fatal crash and 2 fatalities in September 2023. Minor injuries increased in count from 4 to 6, representing a higher share of total crashes at 20% compared to 11.8% in the prior period. Crashes resulting in no injury decreased from 28 to 21, and their share dropped from 82.4% to 70% of all crashes.

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes20%
50.0%prior 4
Possible Injury1possible injury crashes3.3%
0.0%prior 1
No Injury21no injury crashes70%
-25.0%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

Contributing factors show shifts in prevalence; 'No improper driving' increased by 5 crashes, from 6 to 11, becoming the most frequent factor. Conversely, 'Followed too closely' decreased by 6 crashes, from 9 to 3, and 'Failed to yield right of way' decreased by 3 crashes, from 6 to 3. 'Inattention' remained consistent with 3 crashes in both periods.

Officer-Reported Primary Contributing Cause

No improper driving11 (36.7%)83.3%prior 6
Failed to yield right of way3 (10%)-50.0%prior 6
Disregarded traffic signs, signals, road markings3 (10%)
Followed too closely3 (10%)-66.7%prior 9
Inattention3 (10%)
Failure to keep in proper lane or running off road2 (6.7%)
Made an improper turn1 (3.3%)
Driving too fast for conditions1 (3.3%)
Other improper action1 (3.3%)
Over-correcting/over-steering1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions for crashes remained largely consistent, with 'Clear' conditions accounting for 26 crashes in both periods. Crashes occurring in 'Rain' decreased from 6 to 2. Regarding lighting, crashes in 'Daylight' decreased by 4 from 25 to 21, while those in 'Dark - lighted roadway' slightly increased from 6 to 7. Road surface conditions saw a decrease in 'Wet' road crashes from 8 to 2, while 'Dry' road crashes increased from 25 to 27.

Weather

Clear26 (89.7%)
0.0%prior 26
Rain2 (6.9%)
-66.7%prior 6
Cloudy1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight21 (70.0%)
-16.0%prior 25
Dark - lighted roadway7 (23.3%)
16.7%prior 6
Dark - roadway not lighted1 (3.3%)
Dusk1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry27 (93.1%)
8.0%prior 25
Wet2 (6.9%)
-75.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 66 in September 2023 to 50 in September 2024. Toyota became the most frequently involved vehicle make with 6 incidents in the current period, surpassing Ford, which decreased from 10 to 4. Significant shifts in age group representation include an increase of 6 crashes for the 26-34 age group (from 7 to 13) and an increase of 3 crashes for the 65+ age group (from 6 to 9), while the 35-44 age group saw a decrease of 10 crashes, from 15 to 5.

Top Vehicle Makes (50 vehicles)

1
TOYOTA6 (12%)
-14.3%prior 7
2
FORD4 (8%)
-60.0%prior 10
3
JEEP4 (8%)
4
HONDA3 (6%)
-66.7%prior 9
5
SUBARU3 (6%)
6
HYUNDAI3 (6%)
7
KIA3 (6%)
8
VOLVO2 (4%)
9
BMW2 (4%)
10
CADI2 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (51 persons with recorded sex)

Female28 (54.9%)
-15.2%prior 33
Male23 (45.1%)
-47.7%prior 44

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crash distribution across speed zones showed some changes, with no fatal crashes recorded in any speed zone in September 2024, compared to 1 fatal crash in the 20 mph zone in September 2023. Crashes in the 15 mph zone notably increased from 1 to 4, while crashes in the 40 mph zone significantly decreased from 9 to 4. The 30 mph zone remained the most frequent speed limit for crashes, with a slight increase from 11 to 12 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: SOMERSET, MA
  • Total crash records analyzed: 30
  • Total persons involved: 60
  • Total vehicles involved: 50

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/somerset/september-2024-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 — September 2024 | ThatCarHitMe.com