Monthly Traffic Safety Analysis

150 CRASHES IN
LOWELL, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

LOWELL experienced a notable decrease in overall crash incidents in March 2025 compared to March 2024. Total crashes declined by 37.76%, from 241 to 150, while total injuries decreased by 36.26%, from 91 to 58. The most significant year-over-year shift was a 57.14% reduction in DUI-related crashes, which fell from 7 to 3.

150

-37.8%was 241

Total Crash Events

0

Persons Killed

58

-36.3%was 91

Persons Injured

24

-7.7%was 26

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. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in LOWELL showed a significant downward trend year-over-year, with total crashes decreasing from 241 to 150. This represents a 37.76% reduction in crashes. Similarly, total injuries declined by 36.26%, falling from 91 to 58.

24

Hit-and-Run Crashes — March 2025

-7.7% vs prior (26)

The number of hit-and-run crashes decreased slightly from 26 in March 2024 to 24 in March 2025. However, the hit-and-run rate, as a percentage of total crashes, increased from 10.8% in March 2024 to 16% in March 2025, indicating an upward trend in the rate of hit-and-run incidents relative to overall crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 6-16.7%

1

Cyclists Injured

Prior: 10.0%

52

Motorists Injured

Prior: 82-36.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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 Friday in March 2024 (46 crashes) to Monday in March 2025 (30 crashes), despite Monday crashes also decreasing from the prior year's count of 33. The peak hour remained 3 p.m. for both periods, though the number of crashes at this hour decreased from 25 in March 2024 to 18 in March 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either March 2025 or March 2024. While 'Serious Injury' crashes were reported in March 2024 (7 crashes, representing 2.9% of total crashes), this category was not present in March 2025. The proportion of 'No Injury' crashes increased from 66.4% in March 2024 to 70.7% in March 2025, while 'Minor Injury' crashes saw a slight increase in their share from 13.7% to 15.3%.

Outcome by Severity (Crash Events)

Minor Injury23minor injury crashes15.3%
-30.3%prior 33
Possible Injury17possible injury crashes11.3%
-46.9%prior 32
No Injury106no injury crashes70.7%
-33.8%prior 160

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving', decreased in count from 74 in March 2024 to 55 in March 2025. 'Failed to yield right of way' crashes saw a 57.14% reduction in count, dropping from 21 to 9, and its ranking fell from second to third. Conversely, 'Inattention' crashes slightly increased in count from 14 to 15, moving from third to second in ranking among contributing factors.

Officer-Reported Primary Contributing Cause

No improper driving55 (36.7%)-25.7%prior 74
Inattention15 (10%)7.1%prior 14
Failed to yield right of way9 (6%)-57.1%prior 21
Followed too closely8 (5.3%)0.0%prior 8
Failure to keep in proper lane or running off road8 (5.3%)-20.0%prior 10
Other improper action6 (4%)
Disregarded traffic signs, signals, road markings4 (2.7%)-55.6%prior 9
Made an improper turn4 (2.7%)
Distracted3 (2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 169 to 122 year-over-year, while crashes in rainy conditions dropped from 33 to 16. Crashes on dry road surfaces decreased from 187 to 130, and those on wet road surfaces saw a 60% reduction, falling from 50 to 20. Crashes during daylight hours decreased from 169 to 108, and those in dark but lighted roadway conditions decreased from 57 to 35.

Weather

Clear122 (81.3%)
-27.8%prior 169
Rain16 (10.7%)
-51.5%prior 33
Cloudy7 (4.7%)
-69.6%prior 23
Clear/Clear3 (2.0%)
Cloudy/Rain2 (1.3%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight108 (72.0%)
-36.1%prior 169
Dark - lighted roadway35 (23.3%)
-38.6%prior 57
Dawn3 (2.0%)
-40.0%prior 5
Dusk3 (2.0%)
-40.0%prior 5
Dark - roadway not lighted1 (0.7%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry130 (86.7%)
-30.5%prior 187
Wet20 (13.3%)
-60.0%prior 50

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

The age group '65+' experienced the largest decrease in persons involved, falling from 66 to 20. Conversely, the '0-15' age group saw an increase in involvement, from 39 persons to 52. Among top vehicle makes, HONDA became the most frequently involved make in March 2025 with 65 vehicles, surpassing TOYOTA which had 50 vehicles involved, down from 91 in the prior year.

Top Vehicle Makes (286 vehicles)

1
HONDA65 (22.7%)
-18.8%prior 80
2
TOYOTA50 (17.5%)
-45.1%prior 91
3
FORD25 (8.7%)
-40.5%prior 42
4
CHEVROLET20 (7%)
-44.4%prior 36
5
NISSAN18 (6.3%)
-14.3%prior 21
6
HYUNDAI14 (4.9%)
-12.5%prior 16
7
ACURA12 (4.2%)
-14.3%prior 14
8
GMC10 (3.5%)
66.7%prior 6
9
JEEP9 (3.1%)
-43.8%prior 16
10
MAZDA7 (2.4%)
-12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (371 persons with recorded sex)

Male207 (55.8%)
-37.3%prior 330
Female164 (44.2%)
-25.1%prior 219

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed limit zone increased in count from 123 in March 2024 to 135 in March 2025. In contrast, crashes in the 30 mph zone saw a substantial decrease, falling from 77 to 5. There were no fatal crashes recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: LOWELL, MA
  • Total crash records analyzed: 150
  • Total persons involved: 432
  • Total vehicles involved: 286

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: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/march-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 — March 2025 | ThatCarHitMe.com