ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LOWELL, MA · JANUARY 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/january-2025-report
Monthly Traffic Safety Analysis
198 CRASHES IN
LOWELL, MA
JANUARY 2025
In January 2025, Lowell experienced 198 total crashes, an increase from 168 crashes in January 2024, representing a 17.86% rise year-over-year. The most notable shift was a significant increase in total injuries, which rose by 110% from 30 in the prior period to 63 in the current period. There were no fatalities reported in either period.
198
▲ 17.9%was 168
Total Crash Events
0
Persons Killed
63
▲ 110.0%was 30
Persons Injured
20
▲ 5.3%was 19
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. 5 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in Lowell increased year-over-year, rising from 168 crashes in January 2024 to 198 crashes in January 2025. This represents an increase of 17.86% in total crashes. Total injuries also saw a substantial increase of 110%, from 30 to 63, while fatalities remained at zero in both periods.
20
Hit-and-Run Crashes — January 2025
▲ 5.3% vs prior (19)
The number of hit-and-run crashes increased slightly from 19 in January 2024 to 20 in January 2025. Despite this minor increase in count, the overall hit-and-run crash rate decreased from 11.3% to 10.1% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
5
Pedestrians Injured
58
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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, which had 39 crashes in January 2024, to Friday, with 38 crashes in January 2025. Crashes on Fridays increased by 123.5%, from 17 to 38 year-over-year. The peak hour for crashes also changed from 3 PM, with 17 crashes in the prior period, to 8 AM, with 20 crashes in the current period, representing a 150% increase for 8 AM crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Total injuries increased by 110% year-over-year, from 30 in January 2024 to 63 in January 2025. While no fatal crashes occurred in either period, minor injuries (Code B) increased by 58.3% from 12 to 19, and possible injuries (Code C) saw a 187.5% increase, rising from 8 to 23. Crashes resulting in no injury (Code O) also increased significantly by 75.6%, from 86 to 151.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, "No improper driving," increased by 57.4% in count, from 47 crashes (28% share) in the prior period to 74 crashes (37.4% share) in the current period. Crashes attributed to "Inattention" rose by 80% in count, from 10 to 18, and "Failed to yield right of way" increased by 83.3% in count, from 6 to 11. Conversely, "Followed too closely" decreased by 42.9% in count, from 7 crashes (4.2% share) to 4 crashes (2% share).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Clear" weather conditions increased by 75.6%, from 86 to 151, while those in "Snow" conditions decreased by 44.4%, from 36 to 20. Crashes during "Daylight" increased by 26.7%, from 90 to 114, whereas crashes in "Dark - lighted roadway" decreased by 8.5%, from 71 to 65. Regarding road surface, "Dry" conditions saw a 68.2% increase in crashes from 85 to 143, while "Wet" conditions experienced a 31.4% decrease from 35 to 24.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 26.5%, from 313 in January 2024 to 396 in January 2025. Toyota remained the most frequently involved make, with its count increasing by 29.7% from 64 to 83, and Honda saw a 52.9% increase from 51 to 78. Notably, the 16-20 age group experienced a 173.3% increase in persons involved, rising from 15 to 41, and the 21-25 age group increased by 100%, from 31 to 62. The number of males involved in crashes increased by 86.9% from 137 to 256, and females involved increased by 86% from 100 to 186.
Top Vehicle Makes (396 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
60 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (442 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones increased substantially by 440%, from 30 in the prior period to 162 in the current period. In contrast, crashes in 30 mph zones decreased by 87.6%, from 105 to 13. Crashes in 65 mph zones saw a modest increase of 16.7%, rising from 6 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: LOWELL, MA
- Total crash records analyzed: 198
- Total persons involved: 499
- Total vehicles involved: 396
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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/january-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: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved