Monthly Traffic Safety Analysis

8 CRASHES IN
LOWELL, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

Total crashes in Lowell decreased by 96.14% year-over-year, from 207 in December 2024 to 8 in December 2025. This dramatic reduction in overall crash incidents is the most notable shift. Total injuries also saw a substantial decrease, from 68 to 1.

8

▼ -96.1%was 207

Total Crash Events

0

Persons Killed

1

▼ -98.5%was 68

Persons Injured

0

▼ -100.0%was 22

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant decrease in crash activity in Lowell, MA, year-over-year. Total crashes fell by 199 incidents, representing a 96.14% reduction from December 2024 to December 2025. Similarly, total injuries decreased by 67, from 68 to 1.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

1

Motorists Injured

Prior: 60↓-98.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Tuesday in December 2024, with 37 incidents, to Friday in December 2025, with 3 incidents. The peak crash hour also changed, moving from 5 p.m. (19 crashes) in the prior period to 4 p.m. (2 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes were recorded in either December 2024 or December 2025. The proportion of crashes resulting in any injury decreased from 23.7% (49 out of 207 crashes) in the prior period to 12.5% (1 out of 8 crashes) in the current period. The single injury in December 2025 was classified as a possible injury.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes12.5%
↓-95.7%prior 23
No Injury7no injury crashes87.5%
↓-95.4%prior 151

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' decreased by 58 crashes, from 59 in December 2024 to 1 in December 2025. 'Inattention' also saw a significant reduction of 16 crashes, from 17 to 1 year-over-year. While 'Driving too fast for conditions' decreased in count from 3 to 2 crashes, its share of all crashes increased from 1.4% in the prior period to 25% in the current period.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions2 (25%)
Followed too closely2 (25%)↓-71.4%prior 7
Exceeded authorized speed limit1 (12.5%)
Glare1 (12.5%)↓-80.0%prior 5
Inattention1 (12.5%)↓-94.1%prior 17
No improper driving1 (12.5%)↓-98.3%prior 59

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in daylight increased from 50.7% in December 2024 to 62.5% in December 2025. Crashes on snowy or icy road surfaces saw a proportional increase, accounting for 37.5% of crashes in the current period compared to 8.2% in the prior period. While the number of crashes in clear weather decreased from 146 to 5, these conditions still represented the majority of crashes in both periods.

Weather

Clear3 (37.5%)
↓-97.9%prior 140
Clear/Clear2 (25.0%)
↓-66.7%prior 6
Snow1 (12.5%)
↓-90.9%prior 11
Snow/Cloudy1 (12.5%)
Snow/Snow1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight5 (62.5%)
↓-95.2%prior 105
Dark - lighted roadway1 (12.5%)
↓-98.7%prior 79
Dark - roadway not lighted1 (12.5%)
↓-83.3%prior 6
Dusk1 (12.5%)
↓-87.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry5 (62.5%)
↓-96.4%prior 139
Snow2 (25.0%)
↓-83.3%prior 12
Ice1 (12.5%)
↓-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (18 vehicles)

1
TOYOTA4 (22.2%)
↓-95.1%prior 82
2
SUBARU3 (16.7%)
↓-78.6%prior 14
3
VOLVO2 (11.1%)
4
CHEVROLET1 (5.6%)
↓-95.2%prior 21
5
FORD1 (5.6%)
↓-97.9%prior 47
6
HONDA1 (5.6%)
↓-98.7%prior 77
7
ACURA1 (5.6%)
↓-92.3%prior 13
8
KIA1 (5.6%)
↓-93.3%prior 15
9
TESL1 (5.6%)
10
JEEP1 (5.6%)
↓-92.3%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records

Sex Distribution (19 persons with recorded sex)

Male13 (68.4%)
↓-95.0%prior 258
Female6 (31.6%)
↓-97.1%prior 210

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

In December 2025, crashes were recorded exclusively in 25 mph (2 crashes) and 65 mph (4 crashes) speed zones, a narrower distribution compared to December 2024 which saw crashes across eight different speed limits. The 65 mph zone accounted for 50% of crashes in the current period, a significant proportional increase from 2.4% in the prior period. The number of crashes in the 25 mph zone decreased from 179 to 2 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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: 2025-12-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: LOWELL, MA
  • Total crash records analyzed: 8
  • Total persons involved: 19
  • Total vehicles involved: 18

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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/december-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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Lowell, MA Crash Report — December 2025 | ThatCarHitMe.com