Monthly Traffic Safety Analysis

23 CRASHES IN
UXBRIDGE, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

In UXBRIDGE, MA, March 2022 saw a 15% increase in total crashes, rising from 20 in March 2021 to 23. Concurrently, total injuries increased by 40%, from 5 to 7. A notable shift was the appearance of 2 hit-and-run crashes in the current period, compared to none in the prior year.

23

15.0%was 20

Total Crash Events

0

Persons Killed

7

40.0%was 5

Persons Injured

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity year-over-year, with total crashes rising by 15% from 20 to 23. Total injuries also saw a significant increase of 40%, from 5 in the prior period to 7 in the current period.

2

Hit-and-Run Crashes — March 2022

8.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 540.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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, though the count decreased from 6 in the prior period to 5 in the current period. The peak hour for crashes shifted from 4 PM with 4 crashes in the prior period to 1 PM and 2 PM, each with 4 crashes, in the current period. Mondays and Tuesdays experienced increased crash counts, rising from 3 to 5 and 1 to 4 respectively, while Sundays saw a decrease from 3 to 1 crash.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either period. Total injuries increased by 40%, from 5 in the prior period to 7 in the current period. The proportion of crashes resulting in 'Minor Injury' slightly increased from 20% to 21.7%, and 'Possible Injury' crashes, not present in the prior period, accounted for 8.7% of crashes in the current period.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes21.7%
25.0%prior 4
Possible Injury2possible injury crashes8.7%
No Injury16no injury crashes69.6%
6.7%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' increased significantly from 2 in the prior period to 6 in the current period, representing a 200% increase in count. Conversely, 'Inattention' crashes decreased by 50% in count, from 4 to 2. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' crashes also decreased by 33.3% in count, from 3 to 2.

Officer-Reported Primary Contributing Cause

No improper driving6 (26.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (8.7%)
Inattention2 (8.7%)
Glare1 (4.3%)
Made an improper turn1 (4.3%)
Distracted1 (4.3%)
Other improper action1 (4.3%)
Over-correcting/over-steering1 (4.3%)
Physical impairment1 (4.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather remained the dominant condition for crashes, with counts increasing from 15 in the prior period to 19 in the current period. Crashes occurring in daylight conditions also increased from 16 to 19 year-over-year. The number of crashes on wet road surfaces remained constant at 3 in both periods.

Weather

Clear19 (82.6%)
26.7%prior 15
Cloudy1 (4.3%)
Cloudy/Rain1 (4.3%)
Rain1 (4.3%)
Rain/Snow1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight19 (82.6%)
18.8%prior 16
Dark - roadway not lighted3 (13.0%)
Dusk1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry20 (87.0%)
17.6%prior 17
Wet3 (13.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (36 vehicles)

1
CHEVROLET5 (13.9%)
2
SUBARU5 (13.9%)
3
BUIC3 (8.3%)
4
FORD3 (8.3%)
5
NISSAN3 (8.3%)
6
KIA2 (5.6%)
7
HONDA2 (5.6%)
8
TOYOTA2 (5.6%)
9
HYUNDAI1 (2.8%)
10
KW1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (35 persons with recorded sex)

Female19 (54.3%)
35.7%prior 14
Male16 (45.7%)
-15.8%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones doubled from 3 in the prior period to 6 in the current period. Similarly, crashes in 35 mph zones increased significantly from 2 to 6. Conversely, crashes in 65 mph zones decreased by 60%, from 5 to 2, indicating a shift in crash distribution towards lower and moderate speed limits.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: UXBRIDGE, MA
  • Total crash records analyzed: 23
  • Total persons involved: 39
  • Total vehicles involved: 36

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: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/uxbridge/march-2022-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 — March 2022 | ThatCarHitMe.com