ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ARLINGTON, 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/arlington/2025-annual-report
Yearly Traffic Safety Analysis
443 CRASHES IN
ARLINGTON, MA
2025
In 2025, Arlington recorded 443 total traffic crashes, a 17.2% increase from the 378 crashes reported in 2024. While the number of fatal crashes decreased from two to one, the number of persons injured rose by 30.4%, from 79 to 103. The most significant shift was a 53% increase in the count of crashes attributed to a driver failing to yield the right of way, which grew from 47 incidents in 2024 to 72 in 2025.
443
▲ 17.2%was 378
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
103
▲ 30.4%was 79
Persons Injured
65
▲ 25.0%was 52
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. 50 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 traffic safety trends in Arlington show a rise in crashes year-over-year. Total collisions increased by 17.2%, from 378 in 2024 to 443 in 2025. This increase was accompanied by a 30.4% rise in total injuries (from 79 to 103), though total fatalities declined from two to one.
65
Hit-and-Run Crashes — 2025
▲ 25.0% vs prior (52)
Hit-and-run crashes increased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run incidents rose from 52 in 2024 to 65 in 2025, a 25% increase. The hit-and-run rate also trended upward, increasing from 13.8% of all crashes in the prior year to 14.7% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
9
Pedestrians Injured
15
Cyclists Injured
78
Motorists Injured
1
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 temporal patterns of crashes showed some changes between the two periods. While the peak hour for collisions remained consistent at 5 p.m. in both years, the peak day shifted. In 2024, Wednesday was the busiest day with 73 crashes, whereas in 2025, Monday and Wednesday tied for the most crashes, with 71 incidents each. Additionally, crashes during the 8 a.m. hour increased from 26 to 39 year-over-year.
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
The severity of crashes shifted year-over-year. The number of fatal crashes decreased from two in 2024 to one in 2025, and serious injury crashes also fell from 12 to five. However, minor injury crashes saw a substantial increase, rising from 35 incidents in 2024 to 60 in 2025. Consequently, the share of crashes resulting in minor injuries grew from 9.3% to 13.5% of all collisions.
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
Comparing contributing factors, 'Failed to yield right of way' remained the most common cited driver action after 'No improper driving' and saw a significant increase. The count of crashes involving this factor rose from 47 in 2024 to 72 in 2025, a 53.2% increase in count. Crashes attributed to 'Inattention' also increased by 32% in count, from 25 to 33 incidents. 'Followed too closely' incidents grew from 17 to 22, a 29.4% increase in count.
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
While the majority of crashes in both years occurred in daylight and on dry roads, there was a notable increase in crashes under adverse conditions. The number of collisions on wet roads increased by 63.8%, from 47 in 2024 to 77 in 2025. Similarly, crashes during rainy weather increased from 33 to 49. The proportion of crashes in daylight remained stable, accounting for 69.5% of crashes in 2025 compared to 70.4% in 2024.
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—Toyota, Honda, and Subaru—remained consistent across both years, with each make seeing an increase in crash involvement. Toyota-involved crashes rose from 128 to 144, Honda from 91 to 112, and Subaru from 55 to 60. Analysis of persons involved shows a significant increase in the 0-15 age group, whose count more than doubled from 33 in 2024 to 90 in 2025.
Top Vehicle Makes (789 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
140 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (859 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 changed between the two periods. The number of crashes in 25 mph zones increased substantially, from 268 in 2024 to 352 in 2025, accounting for most of the year's total increase. Conversely, crashes in 30 mph zones decreased from 47 to 17. The single fatal crash in 2025 occurred in a 25 mph zone, whereas in 2024, one fatal crash occurred in a 25 mph zone and another in a 35 mph zone.
Fatal crashes by zone: 25 mph: 1 of 352 (0.284%)
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: ARLINGTON, MA
- Total crash records analyzed: 443
- Total persons involved: 993
- Total vehicles involved: 789
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). "ARLINGTON, 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/arlington/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