ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DUXBURY, 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/duxbury/2024-annual-report
Yearly Traffic Safety Analysis
227 CRASHES IN
DUXBURY, MA
2024
In 2024, Duxbury recorded 227 total traffic crashes, a 2.7% increase from the 221 crashes reported in 2023. While total fatalities remained unchanged at two, the number of injuries rose from 66 to 73. The most notable year-over-year shift was a significant increase in crashes attributed to inattention, with the count of such incidents rising 81% from 21 to 38.
227
▲ 2.7%was 221
Total Crash Events
2
Persons Killed
73
▲ 10.6%was 66
Persons Injured
9
▲ 50.0%was 6
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. 3 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 traffic crashes in Duxbury saw a slight increase year-over-year, rising 2.7% from 221 in 2023 to 227 in 2024. This was accompanied by a more pronounced 10.6% rise in total injuries, which grew from 66 to 73. The number of total fatalities remained unchanged at two for both periods.
9
Hit-and-Run Crashes — 2024
▲ 50.0% vs prior (6)
The number of hit-and-run incidents increased by 50% year-over-year, rising from 6 crashes in 2023 to 9 crashes in 2024. The hit-and-run rate, which measures the proportion of total crashes that are hit-and-runs, also trended upward. This rate increased from 2.7% in the prior year to 4.0% in the current year.
Vulnerable Road User Casualties
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
1
Cyclists Injured
71
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 pattern of crashes shifted between the two periods. In 2024, Friday was the peak day for crashes with 43 incidents, a change from 2023 when Tuesday was the peak day with 42 crashes. The peak hour for collisions remained consistent at 4 p.m. in both years, though the number of crashes during that hour increased from 21 to 24.
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 number of fatal crashes remained constant at two in both 2023 and 2024, resulting in a slightly lower fatal crash rate of 0.88 per 100 crashes in the current year compared to 0.90 in the prior year. However, there was a notable rise in serious injury crashes, which increased from 1 in 2023 to 6 in 2024. The share of crashes resulting in no injury decreased from 77.8% to 72.7% year-over-year.
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
While 'No improper driving' was a leading factor in both periods, its count decreased from 70 to 59. The most significant year-over-year change was the rise of 'Inattention' as a contributing factor, with incidents increasing 81% in count from 21 in 2023 to 38 in 2024, moving it from the third to the second most common factor. Similarly, crashes attributed to 'Followed too closely' grew by 63% in count, from 19 to 31 incidents. Conversely, crashes involving 'Failed to yield right of way' decreased by 46% in count, from 37 to 20.
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
In 2024, a larger proportion of crashes occurred in clear conditions compared to the previous year, with the share of incidents in clear weather rising from 67.4% to 74.9%. The share of crashes taking place during daylight hours also rose significantly, from 58.4% in 2023 to 71.8% in 2024. Correspondingly, crashes on dry road surfaces became more common, accounting for 85.9% of all incidents in 2024, up from a 73.8% share in the prior year.
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 remained the most common vehicle make involved in crashes in both years, with 62 vehicles recorded in each period. Honda's involvement increased substantially, moving from the fifth most common make in 2023 (26 vehicles) to the second in 2024 (46 vehicles). Regarding persons involved, the 35-44 age group saw the largest representation in 2024 with 72 individuals, an increase from 55 in the prior year. This contrasts with 2023, where the 65+ and 16-20 age groups were the most frequently involved.
Top Vehicle Makes (391 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
25 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (428 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
There was a shift in the distribution of crashes across speed zones year-over-year. The number of crashes in the 60 mph zone increased from 70 to 75, while incidents in the 30 mph and 40 mph zones decreased from 61 to 48 and 43 to 27, respectively. The location of fatal crashes also shifted; in 2024, one of the two fatal crashes occurred in a 60 mph zone, whereas in 2023, one occurred in a 30 mph zone.
Fatal crashes by zone: 60 mph: 1 of 75 (1.333%)
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: DUXBURY, MA
- Total crash records analyzed: 227
- Total persons involved: 469
- Total vehicles involved: 391
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). "DUXBURY, 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/duxbury/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