ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LOWELL, 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/lowell/2025-annual-report
Yearly Traffic Safety Analysis
1,097 CRASHES IN
LOWELL, MA
2025
In 2025, Lowell recorded 1,097 total crashes, a 58.5% decrease from the 2,646 crashes reported in 2024. Despite the sharp decline in overall collisions, the number of fatalities increased significantly, rising from one in the prior period to six in the current period. Total injuries also saw a substantial reduction, falling from 920 to 395.
1,097
▼ -58.5%was 2,646
Total Crash Events
6
▲ 500.0%was 1
Persons Killed
395
▼ -57.1%was 920
Persons Injured
160
▼ -51.5%was 330
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 36 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
Crash incidents in Lowell showed a significant downward trend year-over-year, falling by 58.5% from 2,646 in 2024 to 1,097 in 2025. This was accompanied by a 57.1% reduction in total injuries, which dropped from 920 to 395. In contrast to the overall trend, the number of fatalities increased from one to six during the same period.
160
Hit-and-Run Crashes — 2025
▼ -51.5% vs prior (330)
The total number of hit-and-run crashes decreased from 330 in 2024 to 160 in 2025, following the overall decline in collisions. However, the hit-and-run rate, which represents the proportion of total crashes that were hit-and-runs, increased from 12.5% to 14.6%. This indicates that while fewer hit-and-runs occurred, they constituted a larger percentage of all crashes in the current period.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
21
Pedestrians Injured
18
Cyclists Injured
351
Motorists Injured
5
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 shifted year-over-year, with both the peak day and peak hour changing. The day with the most crashes moved from Wednesday (420 crashes) in 2024 to Tuesday (179 crashes) in 2025. Similarly, the peak hour for collisions shifted later in the afternoon, from 3 p.m. in the prior period (239 crashes) to 5 p.m. in the current period (97 crashes).
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 total crashes decreased, the severity of outcomes worsened, with the fatal crash rate increasing from 0.04 to 0.55. The number of fatal crashes rose from one to six year-over-year. The proportion of crashes resulting in serious injuries decreased from 1.4% to 0.7% of all crashes. Conversely, the share of minor injury crashes increased slightly from 13.2% in 2024 to 14.9% in 2025.
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
The leading contributing factors remained consistent across both periods, though their raw counts decreased significantly in line with the overall crash reduction. Crashes attributed to 'Inattention' fell from a count of 213 to 87, and incidents involving 'Failed to yield right of way' dropped from 186 to 62. Despite a drop in count from 800 to 405, the share of crashes where 'No improper driving' was cited as a factor increased from 30.2% to 36.9%.
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
Crashes in both periods predominantly occurred in clear weather on dry roads during daylight hours. However, there was a proportional shift in conditions year-over-year. The share of crashes occurring on wet roads increased from 13.3% in 2024 to 15.1% in 2025. Concurrently, the proportion of crashes on dry roads decreased from 82.7% to 76.2%.
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 vehicle makes involved in crashes remained consistent, with Honda (419 vehicles) and Toyota (397 vehicles) leading in 2025, swapping the top two spots from 2024. The age distribution of persons involved in crashes also remained relatively stable between the two periods. The 26-34 age group was the largest cohort in both years, accounting for 17.1% of persons in 2024 and 16.6% in 2025.
Top Vehicle Makes (2,131 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
354 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,468 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
Crashes in the 25 mph speed zone were most common in both years, though the count dropped from 1,739 to 876. Notably, two fatal crashes occurred in 25 mph zones in 2025, whereas none were recorded in this zone in 2024. The sole fatal crash in 2024 occurred in a 35 mph zone; in 2025, this zone also saw one fatal crash, along with another fatal crash in a 15 mph zone.
Fatal crashes by zone: 15 mph: 1 of 2 (50%) · 25 mph: 2 of 876 (0.228%) · 35 mph: 1 of 18 (5.556%)
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: LOWELL, MA
- Total crash records analyzed: 1,097
- Total persons involved: 2,805
- Total vehicles involved: 2,131
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: 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/lowell/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