Monthly Traffic Safety Analysis

45 CRASHES IN
ARLINGTON, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, Arlington recorded 45 crashes, a 40.6% increase from the 32 crashes reported in May 2024. The most significant year-over-year shift was in hit-and-run incidents, which saw a 400% increase from 2 to 10 crashes.

45

40.6%was 32

Total Crash Events

0

Persons Killed

13

18.2%was 11

Persons Injured

10

400.0%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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for May shows an upward trend year-over-year, with total crashes increasing by 40.6% from 32 in May 2024 to 45 in May 2025. Concurrently, total injuries also rose by 18.2%, from 11 to 13.

10

Hit-and-Run Crashes — May 2025

400.0% vs prior (2)

Hit-and-run crashes increased significantly from 2 in May 2024 to 10 in May 2025, representing a 400% increase. This led to the hit-and-run rate rising from 6.3% to 22.2% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

12

Motorists Injured

Prior: 771.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Wednesday with 10 crashes in May 2024 to Saturday with 11 crashes in May 2025. The peak hour for crashes remained consistent at 5 PM, increasing from 6 crashes in May 2024 to 8 crashes in May 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either May 2024 or May 2025. While total injuries increased from 11 to 13, serious injuries decreased from 1 in May 2024 to 0 in May 2025. Minor injuries increased from 6 to 8, and possible injuries decreased from 3 to 1.

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes17.8%
33.3%prior 6
Possible Injury1possible injury crashes2.2%
-66.7%prior 3
No Injury33no injury crashes73.3%
57.1%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

The number of crashes where 'No improper driving' was a factor remained stable at 15 in both periods. 'Failed to yield right of way' crashes saw a substantial increase, rising from 1 in May 2024 to 8 in May 2025. Additionally, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' appeared as a factor in 4 crashes in May 2025, up from no recorded instances in the prior period's top factors.

Officer-Reported Primary Contributing Cause

No improper driving15 (33.3%)0.0%prior 15
Failed to yield right of way8 (17.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (8.9%)
Inattention4 (8.9%)
Followed too closely3 (6.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.2%)
Visibility obstructed1 (2.2%)
Failure to keep in proper lane or running off road1 (2.2%)
Other improper action1 (2.2%)
Over-correcting/over-steering1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 16 in May 2024 to 26 in May 2025, while crashes in rainy conditions decreased from 2 to 1. Crashes in daylight conditions increased from 30 to 34, but crashes in dark conditions (lighted or unlighted) saw a more pronounced rise, from 1 to 9.

Weather

Clear26 (59.1%)
62.5%prior 16
Clear/Clear7 (15.9%)
-12.5%prior 8
Cloudy/Rain3 (6.8%)
Cloudy2 (4.5%)
Rain/Cloudy2 (4.5%)
Clear/Cloudy1 (2.3%)
Rain/Severe crosswinds1 (2.3%)
Rain1 (2.3%)
Cloudy/Cloudy1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight34 (77.3%)
13.3%prior 30
Dark - lighted roadway7 (15.9%)
Dark - roadway not lighted2 (4.5%)
Dusk1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry36 (81.8%)
38.5%prior 26
Wet8 (18.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 41.4%, from 58 to 82. Toyota remained the most frequently involved make, increasing from 10 to 21 vehicles. Among persons involved, the 55-64 age group saw a notable increase from 6 to 16 individuals, and the number of female persons involved rose from 31 to 56.

Top Vehicle Makes (82 vehicles)

1
TOYOTA21 (25.6%)
110.0%prior 10
2
HONDA12 (14.6%)
50.0%prior 8
3
SUBARU8 (9.8%)
60.0%prior 5
4
CHEVROLET5 (6.1%)
5
MAZDA4 (4.9%)
6
NISSAN4 (4.9%)
7
JEEP4 (4.9%)
8
FORD3 (3.7%)
9
KIA2 (2.4%)
10
LEXUS2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

26 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (103 persons with recorded sex)

Female56 (54.4%)
80.6%prior 31
Male47 (45.6%)
27.0%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones increased from 20 in May 2024 to 35 in May 2025. Conversely, crashes in 30 mph zones decreased from 5 to 3. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: ARLINGTON, MA
  • Total crash records analyzed: 45
  • Total persons involved: 115
  • Total vehicles involved: 82

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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/arlington/may-2025-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

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Arlington, MA Crash Report — May 2025 | ThatCarHitMe.com