ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DUDLEY, 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/dudley/2024-annual-report
Yearly Traffic Safety Analysis
199 CRASHES IN
DUDLEY, MA
2024
In 2024, Dudley recorded 199 total crashes, a 4.7% increase from the 190 crashes reported in 2023. Despite the rise in total incidents, the number of reported injuries saw a substantial decrease, falling 37.3% from 67 in the prior year to 42 in the current year. Additionally, there were no fatalities recorded in 2024, compared to one fatality in 2023.
199
▲ 4.7%was 190
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
42
▼ -37.3%was 67
Persons Injured
3
▼ -50.0%was 6
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. 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
Year-over-year, total crashes in Dudley increased by 4.7%, from 190 to 199. However, the severity of these crashes decreased, with total injuries dropping by 37.3% and fatalities being eliminated from one in the prior year to zero in the current year. This suggests a trend of more frequent but less severe collisions.
3
Hit-and-Run Crashes — 2024
▼ -50.0% vs prior (6)
Hit-and-run incidents decreased between the two periods. The total number of hit-and-run crashes was halved, falling from 6 in 2023 to 3 in 2024. Consequently, the hit-and-run rate as a percentage of all crashes dropped from 3.2% in the prior year to 1.5% in the current year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
41
Motorists 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 showed some shifts between the two periods. In 2024, the peak day for crashes was Friday with 36 incidents, which was also one of the two peak days in 2023 (with 32 incidents). The peak hour for crashes shifted from 2 p.m. in 2023 (19 crashes) to a three-way tie at 2 p.m., 5 p.m., and 6 p.m. in 2024, each with 17 crashes, indicating a broadening of the afternoon and evening collision risk period.
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
Crash severity decreased notably from 2023 to 2024, with the number of fatal crashes dropping from one to zero. The proportion of crashes resulting in any injury fell from 21.6% (41 of 190 crashes) in the prior year to 15.6% (31 of 199 crashes) in the current year. While the count of serious injury crashes increased from two to four, minor injury crashes were reduced from 30 in 2023 to 17 in 2024.
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 ranking of the top three contributing factors remained consistent year-over-year, with 'No improper driving,' 'Inattention,' and 'Failed to yield right of way' leading in both periods. The count of crashes attributed to 'Inattention' increased from 34 to 37 (an 8.8% increase), while 'Failed to yield right of way' rose from 16 to 18 incidents (a 12.5% increase). Notably, crashes involving 'Disregarded traffic signs, signals, road markings' increased from 1 to 7, while those due to 'Followed too closely' were halved, decreasing from 12 to 6.
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 in daylight on dry roads. In 2024, 64.3% of crashes happened during daylight, a slight decrease from 68.9% in 2023. There was a notable increase in the proportion of crashes on adverse road surfaces (wet, snow, or ice), which accounted for 28.1% of incidents in 2024 (56 crashes), compared to 20.0% in 2023 (38 crashes).
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
Toyota and Ford remained the top two vehicle makes involved in crashes in both years, although the count for each decreased in 2024; Toyota-involved crashes dropped from 67 to 57, and Ford from 50 to 39. Regarding driver and passenger demographics, the number of persons aged 65 and older involved in crashes increased from 41 in 2023 to 58 in 2024. This raised their share of total persons involved from 9.7% to 14.4%.
Top Vehicle Makes (330 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (379 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 remained largely consistent year-over-year, with the 35 mph and 30 mph zones accounting for the most incidents in both periods. In 2024, crashes in the 35 mph zone increased to 58 from 52, and crashes in the 30 mph zone rose to 49 from 39. The single fatality recorded in 2023 occurred in a 40 mph zone; in 2024, there were no fatalities recorded in any speed zone.
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: DUDLEY, MA
- Total crash records analyzed: 199
- Total persons involved: 402
- Total vehicles involved: 330
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). "DUDLEY, 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/dudley/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