Monthly Traffic Safety Analysis

14 CRASHES IN
WILLIAMSTOWN, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

In September 2024, Williamstown experienced 14 crashes, identical to the 14 crashes recorded in September 2023. While total crashes remained stable year-over-year, total injuries decreased by 40%, from 5 in the prior period to 3 in the current period. Notably, DUI-related crashes increased from 0 to 1, and speeding-related crashes also rose from 0 to 1.

14

Total Crash Events

0

Persons Killed

3

-40.0%was 5

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

Trend Summary

Overall crash volume in Williamstown remained stable year-over-year, with 14 crashes reported in both September 2024 and September 2023. Fatalities remained at 0 in both periods. However, total injuries saw a notable decrease of 40%, falling from 5 in September 2023 to 3 in September 2024.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

3

Motorists Injured

Prior: 4-25.0%

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 distribution of crashes showed shifts year-over-year. The peak day for crashes changed from Friday in September 2023 (4 crashes) to Thursday in September 2024 (4 crashes). Similarly, the peak hour for crashes shifted from 3 PM with 4 crashes in the prior period to 7 AM with 3 crashes in the current period. Notably, Thursday crashes increased from 0 to 4, while Saturday crashes decreased from 3 to 1.

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

Fatal crashes remained at 0 in both September 2023 and September 2024. The proportion of crashes resulting in any injury decreased from 28.6% (4 crashes) in the prior period to 14.3% (2 crashes) in the current period. Specifically, crashes with possible injuries decreased from 3 to 1, while serious injury crashes appeared in the current period with 1 crash, where only minor injuries were present in the prior period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.1%
Possible Injury1possible injury crashes7.1%
-66.7%prior 3
No Injury11no injury crashes78.6%
10.0%prior 10

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

Analysis of contributing factors reveals shifts in crash causation. 'No improper driving' crashes increased from 4 in September 2023 to 5 in September 2024. Conversely, crashes attributed to 'Inattention' decreased from 3 to 1, and 'Other improper action' decreased from 2 to 1. The factor 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' emerged in September 2024 with 3 crashes, while 'Followed too closely' (1 crash) was present in the prior period but not the current.

Officer-Reported Primary Contributing Cause

No improper driving5 (35.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (21.4%)
Failed to yield right of way2 (14.3%)
Inattention1 (7.1%)
Other improper action1 (7.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (7.1%)

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

Crash conditions showed some changes year-over-year. Crashes occurring in 'Daylight' decreased from 13 in September 2023 to 9 in September 2024, while crashes in 'Dark - lighted roadway' increased from 1 to 3, and 'Dusk' crashes increased from 0 to 2. Regarding weather, crashes in 'Clear' conditions increased from 9 to 12, and crashes in 'Rain' conditions decreased from 1 to 0.

Weather

Clear12 (85.7%)
33.3%prior 9
Cloudy1 (7.1%)
Cloudy/Fog, smog, smoke1 (7.1%)

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

Lighting

Daylight9 (64.3%)
-30.8%prior 13
Dark - lighted roadway3 (21.4%)
Dusk2 (14.3%)

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

Road Surface

Dry12 (85.7%)
0.0%prior 12
Sand, mud, dirt, oil, gravel1 (7.1%)
Wet1 (7.1%)

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

Vehicles & Demographics

Top Vehicle Makes (21 vehicles)

1
TOYOTA4 (19%)
-33.3%prior 6
2
HONDA3 (14.3%)
3
FORD3 (14.3%)
4
SUBARU3 (14.3%)
5
HYUNDAI2 (9.5%)
6
AUDI1 (4.8%)
7
BMW1 (4.8%)
8
MNNI1 (4.8%)
9
CHEVROLET1 (4.8%)
10
DODGE1 (4.8%)

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

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

Sex Distribution (23 persons with recorded sex)

Male14 (60.9%)
0.0%prior 14
Female9 (39.1%)
-25.0%prior 12

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

Fatal crash rates remained at 0 across all speed zones in both periods. Crashes in the 25 mph speed zone decreased from 3 in September 2023 to 1 in September 2024, while crashes in the 30 mph zone increased from 3 to 4. Notably, crashes were reported in 5 mph, 10 mph, and 15 mph zones in the current period, which were not present in the prior period. Conversely, crashes in 20 mph, 45 mph, and 50 mph zones from the prior period were not observed in the current period.

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: WILLIAMSTOWN, MA
  • Total crash records analyzed: 14
  • Total persons involved: 25
  • Total vehicles involved: 21

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). "WILLIAMSTOWN, 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/williamstown/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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Williamstown, MA Crash Report — September 2024 | ThatCarHitMe.com