ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · UXBRIDGE, MA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/uxbridge/2024-annual-report
Yearly Traffic Safety Analysis
322 CRASHES IN
UXBRIDGE, MA
2024
In Uxbridge, total traffic crashes increased from 292 in 2023 to 322 in 2024, a rise of approximately 10.3%. During this period, the number of people killed in crashes doubled from one to two. The most significant shift was in hit-and-run incidents, which saw a 62.5% increase from 16 to 26 crashes year-over-year.
322
▲ 10.3%was 292
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
78
▲ 4.0%was 75
Persons Injured
26
▲ 62.5%was 16
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Uxbridge show an increase year-over-year. Total crashes rose by 10.3% from 292 to 322. The number of people injured increased from 75 to 78, while the number of fatalities doubled from one to two.
26
Hit-and-Run Crashes — 2024
▲ 62.5% vs prior (16)
Hit-and-run crashes saw a significant upward trend. The number of hit-and-run incidents increased by 62.5%, rising from 16 in the prior year to 26 in the current year. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also climbed from 5.5% to 8.1%.
Vulnerable Road User Casualties
2
Motorists Killed
0
Other Killed
77
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained broadly consistent, with Friday continuing as the peak day for incidents in both periods, increasing from 51 to 56 crashes. However, the peak hour for crashes shifted slightly earlier, from 6 p.m. in the prior year (24 crashes) to 5 p.m. in the current year (27 crashes). Crashes on Tuesdays also increased from 50 to 53 incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes saw a notable change, with the number of fatal crashes doubling from one to two, and the corresponding fatal crash rate increasing from 0.34% to 0.62%. While the number of serious injury crashes decreased from four to three, minor injury crashes increased from 40 to 44. The proportion of crashes resulting in no injury increased slightly from 77.1% to 78.9%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The primary contributing factors to crashes remained consistent, with 'No improper driving' being the most common factor in both periods, increasing from 96 to 102 incidents. 'Inattention' remained a top factor but its count decreased from 36 to 33 crashes. A notable increase was observed in crashes attributed to 'Followed too closely,' where the count more than doubled from 6 to 15 incidents, a 150% rise. 'Failed to yield right of way' also increased from 20 to 22 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred during daylight hours on dry roads in clear weather, and these proportions remained relatively stable. In the current year, 77.0% of crashes happened on dry roads, compared to 74.3% in the prior year. There was a slight increase in the proportion of crashes occurring in dark, unlighted conditions, rising from 10.3% of total crashes in the prior year to 13.4% in the current year. The share of crashes on wet roads decreased from 20.2% to 13.4%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Chevrolet holding the top three spots in both years; counts for all three increased, with Toyota involvement growing from 63 to 83 vehicles. Analysis of persons involved in crashes shows a demographic shift, with a notable increase in the 26-34 age group (from 85 to 106 people) and the 35-44 age group (from 82 to 116 people). Conversely, the number of persons in the 16-20 age group involved in crashes decreased from 72 to 58.
Top Vehicle Makes (555 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
59 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (618 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shows a slight shift. Crashes in 30 mph zones increased from 57 to 66, while incidents in 35 mph zones held steady at 63. The single fatal crash in the prior period occurred in a 35 mph zone. In the current period, the two fatal crashes occurred in a 30 mph zone and a 45 mph zone.
Fatal crashes by zone: 30 mph: 1 of 66 (1.515%) · 45 mph: 1 of 31 (3.226%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: UXBRIDGE, MA
- Total crash records analyzed: 322
- Total persons involved: 679
- Total vehicles involved: 555
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/uxbridge/2024-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved