ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · DECEMBER 2022
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/barnstable/december-2022-report
Monthly Traffic Safety Analysis
134 CRASHES IN
BARNSTABLE, MA
DECEMBER 2022
Total crashes in BARNSTABLE, MA increased significantly from 85 in December 2021 to 134 in December 2022, marking a 57.65% rise. This period also saw a notable shift from zero fatalities in December 2021 to one fatality in December 2022. The increase in total crashes is the most prominent year-over-year change.
134
▲ 57.6%was 85
Total Crash Events
1
Persons Killed
32
▲ 10.3%was 29
Persons Injured
6
▲ 100.0%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in BARNSTABLE show a rising trend year-over-year, with total crashes increasing from 85 in December 2021 to 134 in December 2022. This represents a substantial 57.65% increase in crashes. Fatalities also rose from 0 to 1 during this period.
6
Hit-and-Run Crashes — December 2022
▲ 100.0% vs prior (3)
Hit-and-run crashes increased from 3 incidents in December 2021 to 6 incidents in December 2022. The hit-and-run rate also saw an increase, rising from 3.5% of total crashes to 4.5% of total crashes. This indicates an upward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
3
Pedestrians Injured
29
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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 Thursday in both periods, with 46 crashes in December 2022 compared to 19 in December 2021. However, the peak hour shifted from 2 PM with 10 crashes in December 2021 to 7 AM with 17 crashes in December 2022, indicating a change in the busiest time for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution shows a notable change, with the fatal crash rate increasing from 0% in December 2021 (0 fatal crashes) to 0.75% in December 2022 (1 fatal crash). While minor injury crashes remained at 17 incidents in both periods, their proportion of total crashes decreased from 20% to 12.7% due to the overall increase in incidents. Possible injury crashes increased from 4 (4.7% share) to 8 (6% share) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' crashes increased by 17 incidents, from 20 to 37, representing an 85% increase in count. 'Failed to yield right of way' crashes rose by 5 incidents, from 7 to 12, a 71.4% increase in count. 'Inattention' crashes remained constant at 24 incidents in both periods, but its share of total crashes decreased from 28.2% to 17.9%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 55 to 88, and 'Dry' road surface crashes increased from 59 to 86. Crashes during 'Daylight' also rose from 52 to 77 incidents. While the number of crashes in adverse conditions like 'Rain' increased slightly from 14 to 16, and 'Ice' from 5 to 16, the proportion of crashes under 'Clear' and 'Dry' conditions remained dominant.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 83, from 158 in December 2021 to 241 in December 2022, a 52.5% rise. Toyota remained the top vehicle make involved, increasing from 28 to 49 incidents, followed by Ford (24 to 29) and Honda (19 to 27). All age groups experienced an increase in person involvement, with the 65+ age group seeing the largest count increase from 27 to 47 persons.
Top Vehicle Makes (241 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (268 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph speed zones increased from 27 to 37, and in 35 mph zones from 22 to 38. There was a notable increase in crashes in 55 mph zones, rising from 7 to 20 incidents. A fatal crash occurred in a 30 mph zone in December 2022, whereas no fatal crashes were recorded in any speed zone in December 2021.
Fatal crashes by zone: 30 mph: 1 of 37 (2.703%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-12-01 through 2022-12-31 (31 days)
- Geographic scope: BARNSTABLE, MA
- Total crash records analyzed: 134
- Total persons involved: 290
- Total vehicles involved: 241
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). "BARNSTABLE, MA Crash Intelligence Report: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/december-2022-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: 2022-12-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved