ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HUDSON, MA · 2025
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/hudson/2025-annual-report
Yearly Traffic Safety Analysis
312 CRASHES IN
HUDSON, MA
2025
In 2025, Hudson recorded 312 total traffic crashes, a 22.2% decrease from the 401 crashes recorded in 2024. While overall crashes and injuries declined, the most notable shift was an increase in the count and rate of hit-and-run incidents. Fatalities remained at zero for both years.
312
▼ -22.2%was 401
Total Crash Events
0
Persons Killed
94
▼ -13.0%was 108
Persons Injured
12
▲ 33.3%was 9
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic incidents in Hudson is downward year-over-year. Total crashes fell by 22.2%, from 401 in 2024 to 312 in 2025. Similarly, the number of people injured in these crashes decreased by 13.0%, from 108 to 94, while fatalities remained at zero in both periods.
12
Hit-and-Run Crashes — 2025
▲ 33.3% vs prior (9)
The number of hit-and-run crashes increased from 9 in 2024 to 12 in 2025. This represents an upward trend in both count and rate. The hit-and-run rate, as a percentage of total crashes, grew from 2.2% in the prior year to 3.8% in the current year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
6
Cyclists Injured
88
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 Tuesday in both 2025 (53 crashes) and 2024 (66 crashes), though the volume on this day decreased. However, the peak hour for crashes shifted from the 3 PM hour in 2024, which saw 40 incidents, to the 5 PM hour in 2025, which recorded 36 incidents. This suggests a change in the highest-risk time from mid-afternoon to the later part of the evening commute.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either 2025 or 2024. While total crashes decreased, the share of crashes involving serious injuries increased from 2.0% (8 of 401 crashes) in 2024 to 3.5% (11 of 312 crashes) in 2025. Conversely, the proportion of crashes resulting in minor injuries decreased from 15.0% to 11.9% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors were consistent across both periods: 'Inattention', 'Failed to yield right of way', and 'Followed too closely'. The count of crashes attributed to 'Inattention' decreased from 67 in 2024 to 49 in 2025, a 26.9% reduction. Crashes involving a driver who 'Failed to yield right of way' also saw a count decrease from 61 to 52. Notably, crashes attributed to a 'Distracted' driver increased in count from 3 to 9.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both years, the majority of crashes occurred in clear weather and on dry roads. Crashes on wet road surfaces occurred 50 times in both 2024 and 2025, but this represented a higher proportion of total crashes in 2025 (16.0%) compared to 2024 (12.5%). The share of crashes happening in daylight increased from 72.3% in 2024 to 77.6% in 2025, while incidents in dark, lighted roadway conditions decreased from 73 to 42.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Toyota, Ford, and Honda were the top three vehicle makes involved in crashes in both periods, with Toyota consistently being the most frequent. The number of Toyotas in crashes decreased from 128 to 110 year-over-year. An analysis of persons involved shows a stable demographic profile, with the proportional representation of different age groups remaining consistent between 2024 and 2025. For example, the 16-20 age group accounted for 11.8% of persons involved in both years.
Top Vehicle Makes (579 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
46 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (693 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the most common 30 mph speed zone decreased from 198 in 2024 to 152 in 2025. A similar downward trend was observed in higher speed zones, with crashes in 65 mph zones falling from 29 to 14. There were no fatal crashes recorded in any speed zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: HUDSON, MA
- Total crash records analyzed: 312
- Total persons involved: 737
- Total vehicles involved: 579
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). "HUDSON, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hudson/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved