ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LOWELL, MA · FEBRUARY 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/lowell/february-2025-report
Monthly Traffic Safety Analysis
191 CRASHES IN
LOWELL, MA
FEBRUARY 2025
Total crashes in Lowell increased by 2.69% from 186 in February 2024 to 191 in February 2025. Fatalities remained constant at 1 in both periods, while total injuries rose by 3.85% from 52 to 54. The most notable shift was a 250% increase in speeding-related crashes, which rose from 2 to 7.
191
▲ 2.7%was 186
Total Crash Events
1
Persons Killed
54
▲ 3.8%was 52
Persons Injured
28
▲ 16.7%was 24
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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Lowell shows a slight upward trend, with total crashes increasing from 186 in February 2024 to 191 in February 2025. This represents a 2.69% rise in crash incidents year-over-year.
28
Hit-and-Run Crashes — February 2025
▲ 16.7% vs prior (24)
Hit-and-run crashes increased by 16.67% year-over-year, rising from 24 incidents in February 2024 to 28 incidents in February 2025. Consequently, the hit-and-run rate also increased from 12.9% in the prior period to 14.7% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
3
Pedestrians Injured
2
Cyclists Injured
49
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. The peak day for crashes moved from Thursday with 46 crashes in February 2024 to Monday with 35 crashes in February 2025. Similarly, the peak hour for crashes shifted from 5 PM with 20 crashes in February 2024 to 7 PM with 19 crashes in February 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained constant at 1 in both periods, resulting in a slight decrease in the fatal crash rate from 0.54% to 0.52%. Injury crashes (categorized as Serious, Minor, or Possible) collectively increased from 35 in the prior period to 43 in the current period. This led to an increase in the proportion of injury crashes from 18.82% to 22.51% of all crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' increased by 38.98% from 59 crashes to 82 crashes, and its share of total crashes rose from 31.7% to 42.9%. 'Inattention' crashes saw a 160% increase in count, rising from 5 to 13, and 'Driving too fast for conditions' crashes increased by 500% from 1 to 6. Conversely, 'Failed to yield right of way' crashes decreased by 33.33% from 15 to 10, and 'Followed too closely' crashes decreased by 63.64% from 11 to 4.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather conditions played a more significant role in the current period, with snow-related crashes increasing by 360% from 5 to 23, and sleet/hail crashes appearing with 7 incidents, not present in the prior period. Correspondingly, crashes occurring in clear weather decreased by 20.9% from 158 to 125. Road surface conditions also reflected this, with dry road crashes decreasing by 31.88% from 160 to 109, while snow-covered roads saw a 700% increase in crashes from 3 to 24, and ice-covered roads accounted for 19 crashes in the current period, not present in the prior period. Crashes occurring in dark-lighted roadway conditions increased by 42% from 50 to 71.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field
Vehicles & Demographics
The age group 55-64 experienced the largest percentage increase in persons involved in crashes, rising by 66.67% from 27 to 45. There was also a 30.95% increase in the 45-54 age group, from 42 to 55, and a 29.79% increase in the 21-25 age group, from 47 to 61. Among vehicle makes, Subaru crashes increased significantly from 8 to 19, moving it into the top five, while Nissan crashes decreased from 27 to 15, falling out of the top five.
Top Vehicle Makes (373 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records
69 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (405 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased substantially by 385.71%, rising from 35 to 170, and this zone recorded the single fatal crash in the current period. Conversely, crashes in 30 mph zones decreased by 95.9% from 122 to 5, and 35 mph zones saw a 75% decrease from 8 to 2, with the fatal crash in the prior period occurring in a 35 mph zone. This indicates a notable shift of crashes to lower speed limit zones.
Fatal crashes by zone: 25 mph: 1 of 170 (0.588%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-02-01 through 2025-02-28 (28 days)
- Geographic scope: LOWELL, MA
- Total crash records analyzed: 191
- Total persons involved: 474
- Total vehicles involved: 373
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). "LOWELL, MA Crash Intelligence Report: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/february-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-02-01 – 2025-02-28
Generated: June 21, 2026 · All rights reserved