Monthly Traffic Safety Analysis

20 CRASHES IN
UXBRIDGE, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In September 2025, UXBRIDGE experienced 20 total crashes, a 16.67% decrease compared to the 24 crashes reported in September 2024. Total injuries also saw a decrease, falling by 20% from 5 to 4. The most notable year-over-year shift was a 50% reduction in hit-and-run crashes, decreasing from 2 to 1.

20

-16.7%was 24

Total Crash Events

0

Persons Killed

4

-20.0%was 5

Persons Injured

1

-50.0%was 2

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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in UXBRIDGE trended downwards year-over-year. Total crashes decreased by 16.67%, from 24 crashes in September 2024 to 20 crashes in September 2025. Similarly, total injuries declined by 20%, from 5 to 4.

1

Hit-and-Run Crashes — September 2025

-50.0% vs prior (2)

Hit-and-run crashes decreased by 50% year-over-year, from 2 crashes in September 2024 to 1 crash in September 2025. This resulted in a reduction of the hit-and-run rate from 8.3% in the prior period to 5% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 5-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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 significantly year-over-year. In September 2025, Wednesday became the peak day with 8 crashes, up from 1 crash on Wednesdays in September 2024, while Saturday crashes decreased from 5 to 1. The peak hour shifted from 10 AM with 4 crashes in the prior period to 8 AM with 6 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either September 2024 or September 2025. The number of minor injuries (severity B) decreased from 4 in the prior period to 1 in the current period, while serious injuries (severity A) increased from 0 to 1. Crashes resulting in no injury remained the most common outcome, accounting for 75% of crashes in September 2025 and 79.2% in September 2024.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes5%
Minor Injury1minor injury crashes5%
-75.0%prior 4
Possible Injury1possible injury crashes5%
0.0%prior 1
No Injury15no injury crashes75%
-21.1%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' increased by 1 crash, from 8 in September 2024 to 9 in September 2025. 'Failed to yield right of way' saw a notable increase, rising from 1 crash in the prior period to 4 crashes in the current period. 'Inattention' remained constant at 3 crashes in both periods, while 'Followed too closely' was a top factor with 3 crashes in the prior period but was not among the top factors in the current period.

Officer-Reported Primary Contributing Cause

No improper driving9 (45%)12.5%prior 8
Failed to yield right of way4 (20%)
Inattention3 (15%)
Disregarded traffic signs, signals, road markings1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Daylight conditions accounted for a higher proportion of crashes in September 2025, with 17 crashes, compared to 13 in September 2024. Crashes occurring in dark conditions with lighted roadways decreased from 4 to 1. While dry road surfaces remained dominant, crashes on wet surfaces increased from 2 in the prior period to 3 in the current period.

Weather

Clear14 (70.0%)
7.7%prior 13
Clear/Other2 (10.0%)
Clear/Unknown1 (5.0%)
Cloudy/Other1 (5.0%)
Cloudy/Rain1 (5.0%)
Rain1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight17 (85.0%)
30.8%prior 13
Dark - lighted roadway1 (5.0%)
Dark - unknown roadway lighting1 (5.0%)
Dawn1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry17 (85.0%)
-19.0%prior 21
Wet3 (15.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (37 vehicles)

1
FORD7 (18.9%)
2
TOYOTA4 (10.8%)
3
CHEVROLET3 (8.1%)
4
KIA3 (8.1%)
5
BUIC2 (5.4%)
6
DODGE2 (5.4%)
7
HONDA2 (5.4%)
-66.7%prior 6
8
CADI2 (5.4%)
9
AUDI1 (2.7%)
10
VOLVO1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (42 persons with recorded sex)

Male25 (59.5%)
-19.4%prior 31
Female17 (40.5%)
21.4%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 2 in September 2024 to 5 in September 2025. Conversely, crashes in 30 mph zones decreased from 6 to 4 year-over-year. The 65 mph speed zone, which had 6 crashes in the prior period, did not report any crashes in the current period, while 5 mph, 10 mph, and 20 mph zones each reported 1 crash in the current period after having none in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: UXBRIDGE, MA
  • Total crash records analyzed: 20
  • Total persons involved: 49
  • Total vehicles involved: 37

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). "UXBRIDGE, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/uxbridge/september-2025-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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Uxbridge, MA Crash Report — September 2025 | ThatCarHitMe.com