ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DARTMOUTH, MA · FEBRUARY 2026
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/dartmouth/february-2026-report
Monthly Traffic Safety Analysis
58 CRASHES IN
DARTMOUTH, MA
FEBRUARY 2026
In February 2026, Dartmouth experienced 58 total crashes, a decrease of 6.5% compared to the 62 crashes recorded in February 2025. A notable shift was observed in speeding-related crashes, which increased by 133.3%, rising from 6 incidents in the prior period to 14 in the current period.
58
▼ -6.5%was 62
Total Crash Events
0
Persons Killed
27
▲ 8.0%was 25
Persons Injured
5
▲ 150.0%was 2
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes in Dartmouth showed a slight downward trend, decreasing from 62 crashes in February 2025 to 58 crashes in February 2026. This represents a 6.5% reduction in total crash incidents year-over-year.
5
Hit-and-Run Crashes — February 2026
▲ 150.0% vs prior (2)
Hit-and-run crashes increased significantly from 2 incidents in February 2025 to 5 incidents in February 2026, representing a 150% rise. Consequently, the hit-and-run rate also increased, moving from 3.2% of all crashes in the prior period to 8.6% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
26
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday in February 2025, with 14 crashes, to Saturday in February 2026, which recorded 15 crashes. Additionally, the peak crash hour moved from 4 p.m. with 6 crashes in the prior period to 5 p.m. with 7 crashes in the current period. Crashes on Wednesday significantly decreased from 14 to 5, while Saturday crashes increased from 9 to 15.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either February 2025 or February 2026. Total injuries increased slightly from 25 to 27 year-over-year. The proportion of minor injury crashes rose from 17.7% to 27.6%, while possible injury crashes decreased from 12.9% to 3.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor in February 2026 was 'Driving too fast for conditions' with 12 crashes, a 300% increase from 3 crashes in February 2025. Conversely, 'Followed too closely' crashes decreased by 66.7%, from 9 to 3, and 'Failed to yield right of way' crashes decreased by 50%, from 6 to 3. 'Inattention' remained consistent with 10 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 39 to 33, while those in snowy conditions increased from 4 to 12. Correspondingly, crashes on dry road surfaces decreased from 42 to 28, but incidents on snowy road surfaces rose from 7 to 15, and on icy surfaces from 3 to 6. Crashes occurring in dark, unlighted roadway conditions decreased from 12 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes remained stable, with 106 in February 2026 compared to 103 in February 2025. Honda vehicles maintained their top position with 16 involved in both periods, while Nissan vehicles involved in crashes increased from 6 to 11. The age group 35-44 saw an increase in persons involved in crashes, rising from 15 to 23, whereas the 16-20 age group saw a decrease from 28 to 21.
Top Vehicle Makes (106 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (116 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones shifted year-over-year. Crashes in 30 mph zones increased from 18 to 22, while those in 40 mph zones decreased from 19 to 13. Crashes in 65 mph zones also saw a reduction, falling from 9 to 4.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-02-01 through 2026-02-28 (28 days)
- Geographic scope: DARTMOUTH, MA
- Total crash records analyzed: 58
- Total persons involved: 130
- Total vehicles involved: 106
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). "DARTMOUTH, MA Crash Intelligence Report: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dartmouth/february-2026-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: 2026-02-01 – 2026-02-28
Generated: June 21, 2026 · All rights reserved