ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DUXBURY, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
221 CRASHES IN
DUXBURY, MA
2023
In 2023, Duxbury recorded 221 total traffic crashes, an 11.2% decrease from the 249 crashes reported in 2022. While overall collisions and resulting injuries declined, the number of fatalities doubled from one person in 2022 to two in 2023. A notable shift in contributing factors was a 37% increase in the count of crashes attributed to 'Failed to yield right of way'.
221
▼ -11.2%was 249
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
66
▼ -12.0%was 75
Persons Injured
6
▼ -14.3%was 7
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic incidents in Duxbury showed a downward trend year-over-year, with total crashes decreasing by 11.2% from 249 in 2022 to 221 in 2023. This trend included a 12% reduction in total injuries, which fell from 75 to 66. However, fatalities increased from one person killed in 2022 to two in 2023.
6
Hit-and-Run Crashes — 2023
▼ -14.3% vs prior (7)
The number of hit-and-run incidents saw a slight decrease, with 6 crashes reported in 2023 compared to 7 in 2022. The hit-and-run rate as a percentage of total crashes also declined marginally, from 2.8% in 2022 to 2.7% in 2023. These figures indicate a relatively stable and slightly downward trend for hit-and-run crashes.
Vulnerable Road User Casualties
0
Cyclists Killed
2
Motorists Killed
2
Cyclists Injured
64
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In 2023, the peak day for crashes was Tuesday with 42 incidents, a change from 2022 when Saturday was the peak day with 43 incidents. The peak hour for collisions also shifted slightly earlier, from 5 PM in 2022 (25 crashes) to 4 PM in 2023 (21 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the fatal crash rate as a percentage of all crashes increased from 0.4% in 2022 to 0.9% in 2023. Conversely, the proportion of crashes resulting in serious injuries dropped significantly, from 2.4% of all crashes in 2022 to 0.5% in 2023. The share of crashes with no reported injuries increased from 73.5% in 2022 to 77.8% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading cited factor in both years was 'No improper driving,' with counts remaining stable at 70 in 2023 versus 73 in 2022. Crashes attributed to 'Failed to yield right of way' increased by 37% in count, rising from 27 incidents in 2022 to 37 in 2023. In contrast, crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a 68.8% decrease in count, from 16 in 2022 to 5 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly similar year-over-year, with the majority of incidents in both 2023 and 2022 occurring in clear weather and during daylight hours. In 2023, 73.8% of crashes happened on dry roads, a slight decrease from 79.1% in 2022, with a corresponding increase in the proportion of crashes on wet roads. There was a notable decrease in crashes occurring in dark, unlighted roadway conditions, which fell from 67 incidents in 2022 to 42 in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The composition of vehicles involved in crashes remained consistent, with Toyota and Ford being the top two makes in both 2023 and 2022 with nearly identical counts. Analysis of persons involved shows a demographic shift, as the 65+ age group saw its involvement increase from 63 individuals in 2022 to 72 in 2023, becoming the largest cohort. Conversely, the number of persons aged 16-20 involved in crashes decreased from 80 to 71 over the same period.
Top Vehicle Makes (373 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (420 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted between the two years. In 2022, the 30 mph zone saw the most crashes (85), but this number fell to 61 in 2023, making the 60 mph zone the most frequent location for crashes (70 incidents). The single fatal crash in 2022 occurred in a 60 mph zone, while one of the two fatal crashes in 2023 occurred in a 30 mph zone.
Fatal crashes by zone: 30 mph: 1 of 61 (1.639%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: DUXBURY, MA
- Total crash records analyzed: 221
- Total persons involved: 447
- Total vehicles involved: 373
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/duxbury/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved