ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · DARTMOUTH, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
584 CRASHES IN
DARTMOUTH, MA
2025
In 2025, Dartmouth recorded 584 total vehicle crashes, a 1.7% decrease from the 594 crashes reported in 2024. Despite the slight drop in overall collisions, the number of fatalities increased significantly, rising from 2 in 2024 to 11 in 2025. This represents a 450% year-over-year increase in traffic-related deaths.
584
▼ -1.7%was 594
Total Crash Events
11
▲ 450.0%was 2
Persons Killed
236
▼ -6.7%was 253
Persons Injured
26
▼ -13.3%was 30
Hit-and-Run Crashes
Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Dartmouth showed a slight decline in 2025, with total crashes decreasing by 1.7% from 594 to 584. The number of people injured in these incidents also fell by 6.7%, from 253 in 2024 to 236 in 2025. In contrast to these trends, fatalities saw a sharp increase from 2 to 11 year-over-year.
26
Hit-and-Run Crashes — 2025
▼ -13.3% vs prior (30)
Hit-and-run incidents saw a decrease in 2025 compared to the previous year. The total number of hit-and-run crashes fell from 30 in 2024 to 26 in 2025. This corresponds to a decline in the hit-and-run rate, which dropped from 5.1% of all crashes in 2024 to 4.5% in 2025.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
10
Motorists Killed
0
Other Killed
5
Pedestrians Injured
3
Cyclists Injured
224
Motorists Injured
4
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2025, the peak day for crashes was Monday with 110 incidents, a change from Thursday (100 incidents) in 2024. The peak hour also shifted slightly earlier, from the 6 PM hour in 2024 to the 5 PM hour in 2025, which recorded 48 crashes. The afternoon commute hours from 3 PM to 6 PM remained a high-frequency period for collisions in both years.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the overall number of crashes decreased, their severity worsened significantly in 2025. The number of fatal crashes quadrupled from 2 in 2024 to 8 in 2025, causing the fatal crash rate to increase from 0.34% to 1.37%. The count of serious injury crashes also rose from 15 to 19. Conversely, crashes resulting in minor injuries decreased from 132 to 116 year-over-year.
Severity is per crash event (most severe injury). 8 fatal crash events resulted in 11 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
Driver inattention remained the leading contributing factor in both periods, with the count of related crashes increasing by 25% from 108 in 2024 to 135 in 2025. Conversely, crashes attributed to 'Failed to yield right of way' decreased in count by 29% from 100 to 71, causing it to drop from the second to the third most common factor. The count for crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also increased from 32 to 40.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained broadly similar year-over-year, with the vast majority of incidents in both periods occurring on dry roads in clear or cloudy weather. In 2025, 81.7% of crashes happened on dry roads, nearly identical to 81.0% in 2024. There was a minor shift in lighting conditions, with the proportion of crashes in daylight increasing from 66.2% in 2024 to 69.3% in 2025, while crashes in dark conditions decreased proportionally.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford leading in both 2024 and 2025. Toyota-involved crashes increased from 151 to 169, while incidents involving Honda and Ford vehicles saw minor decreases. Analysis of persons involved shows a decrease in the 26-34 age group (from 192 to 167) and the 45-54 age group (from 150 to 132). Conversely, the number of individuals aged 0-15 involved in crashes rose from 72 to 91.
Top Vehicle Makes (1,029 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
88 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,219 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained largely unchanged, with zones posted at 30 mph and 40 mph accounting for the highest volume of incidents in both years. However, the location of fatal crashes shifted dramatically. In 2025, five fatal crashes occurred in 65 mph zones, and two occurred in 35 mph zones; no fatal crashes were recorded in these specific zones in 2024. The prior year's two fatal crashes were in 30 mph and 40 mph zones.
Fatal crashes by zone: 35 mph: 2 of 96 (2.083%) · 40 mph: 1 of 181 (0.552%) · 65 mph: 5 of 61 (8.197%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: DARTMOUTH, MA
- Total crash records analyzed: 584
- Total persons involved: 1,317
- Total vehicles involved: 1,029
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/dartmouth/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved