Yearly Traffic Safety Analysis

2,646 CRASHES IN
LOWELL, MA
2024

All metrics benchmarked against2023

In 2024, Lowell recorded 2,646 total traffic crashes, a 17.9% increase from the 2,245 crashes documented in 2023. While the number of fatalities remained stable at one, the total number of injuries rose significantly from 698 to 920, marking a 31.8% year-over-year increase.

2,646

17.9%was 2,245

Total Crash Events

1

Persons Killed

920

31.8%was 698

Persons Injured

330

-9.6%was 365

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Lowell showed a rising trend in 2024 compared to the previous year. The total number of crashes increased by 17.9%, from 2,245 to 2,646. This upward trend was also reflected in crash outcomes, with total injuries increasing by 31.8% year-over-year.

330

Hit-and-Run Crashes — 2024

-9.6% vs prior (365)

Hit-and-run incidents showed a notable decrease in 2024 compared to the previous year. The total number of hit-and-run crashes fell from 365 in 2023 to 330 in 2024. This decline was also reflected in the hit-and-run rate, which dropped from 16.3% of all crashes in 2023 to 12.5% in 2024.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 10.0%

0

Other Killed

Prior: 00.0%

55

Pedestrians Injured

Prior: 4619.6%

34

Cyclists Injured

Prior: 2070.0%

821

Motorists Injured

Prior: 62730.9%

10

Other Injured

Prior: 5100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. While Wednesday remained the peak day for crashes in both 2024 (420 crashes) and 2023 (341 crashes), the peak hour for collisions moved earlier in the day. In 2024, the most crashes occurred during the 3 PM hour (239 crashes), a shift from the 5 PM peak hour observed in 2023 (199 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes remained unchanged at one in both 2024 and 2023. However, the proportion of crashes resulting in some form of injury increased, rising from 21.6% of all crashes in 2023 to 25.2% in 2024. This was driven by increases in the share of both minor injuries (from 10.6% to 13.2%) and possible injuries (from 9.5% to 10.6%).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0%
0.0%prior 1
Serious Injury37serious injury crashes1.4%
19.4%prior 31
Minor Injury350minor injury crashes13.2%
46.4%prior 239
Possible Injury280possible injury crashes10.6%
30.8%prior 214
No Injury1,818no injury crashes68.7%
27.5%prior 1,426

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained broadly consistent, though counts for most factors increased with the overall rise in crashes. Crashes attributed to 'Inattention' grew by 44.9% in count, from 147 in 2023 to 213 in 2024, making it the top improper driving factor. Similarly, crashes involving 'Failed to yield right of way' increased in count by 36.8% from 136 to 186. The count for crashes where drivers 'Followed too closely' remained unchanged at 138 for both years.

Officer-Reported Primary Contributing Cause

No improper driving800 (30.2%)19.0%prior 672
Inattention213 (8%)44.9%prior 147
Failed to yield right of way186 (7%)36.8%prior 136
Followed too closely138 (5.2%)0.0%prior 138
Disregarded traffic signs, signals, road markings89 (3.4%)21.9%prior 73
Failure to keep in proper lane or running off road86 (3.3%)36.5%prior 63
Other improper action51 (1.9%)70.0%prior 30
Distracted43 (1.6%)43.3%prior 30
Made an improper turn35 (1.3%)66.7%prior 21
Driving too fast for conditions30 (1.1%)30.4%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In 2024, a larger proportion of crashes occurred under favorable conditions compared to the prior year. Crashes on dry road surfaces accounted for 82.7% of the total in 2024, up from a 75.4% share in 2023. Correspondingly, crashes on wet roads decreased in both absolute count (from 435 to 351) and as a percentage of total crashes. A similar trend was observed in weather conditions, with 77.9% of crashes happening in clear weather in 2024, compared to 65.0% in 2023.

Weather

Clear2,062 (78.8%)
41.3%prior 1,459
Rain201 (7.7%)
-2.9%prior 207
Cloudy188 (7.2%)
12.6%prior 167
Snow58 (2.2%)
34.9%prior 43
Clear/Clear29 (1.1%)
-79.0%prior 138
Cloudy/Rain19 (0.7%)
-66.7%prior 57
Rain/Cloudy13 (0.5%)
-45.8%prior 24
Sleet, hail (freezing rain or drizzle)8 (0.3%)
33.3%prior 6
Clear/Cloudy7 (0.3%)
-22.2%prior 9
Rain/Rain6 (0.2%)
-71.4%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight1,769 (67.4%)
21.0%prior 1,462
Dark - lighted roadway693 (26.4%)
15.9%prior 598
Dusk65 (2.5%)
30.0%prior 50
Dark - roadway not lighted51 (1.9%)
-20.3%prior 64
Dawn31 (1.2%)
14.8%prior 27
Dark - unknown roadway lighting13 (0.5%)
8.3%prior 12
Other1 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry2,189 (83.5%)
29.4%prior 1,692
Wet351 (13.4%)
-19.3%prior 435
Snow52 (2.0%)
0.0%prior 52
Ice17 (0.6%)
88.9%prior 9
Slush7 (0.3%)
Sand, mud, dirt, oil, gravel2 (0.1%)
Other1 (0.0%)
Water (standing, moving)1 (0.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford holding the top three spots in both 2023 and 2024. When examining the age of individuals involved in crashes, there was a notable increase in the representation of persons aged 26-34, whose share grew from 14.5% in 2023 to 17.1% in 2024. The 35-44 age group also saw its share of involvement increase from 13.6% to 14.9%.

Top Vehicle Makes (5,090 vehicles)

1
TOYOTA944 (18.5%)
19.8%prior 788
2
HONDA919 (18.1%)
22.9%prior 748
3
FORD529 (10.4%)
26.9%prior 417
4
CHEVROLET343 (6.7%)
18.7%prior 289
5
NISSAN304 (6%)
7.8%prior 282
6
JEEP172 (3.4%)
17.8%prior 146
7
SUBARU167 (3.3%)
33.6%prior 125
8
HYUNDAI165 (3.2%)
34.1%prior 123
9
ACURA132 (2.6%)
1.5%prior 130
10
KIA127 (2.5%)
46.0%prior 87

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

1,052 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,655 persons with recorded sex)

Male3,158 (55.8%)
27.0%prior 2,487
Female2,497 (44.2%)
28.0%prior 1,951

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

A significant shift occurred in the reported speed zones where crashes took place. In 2024, 69.1% of crashes with a recorded speed limit occurred in 25 mph zones, a substantial increase from a 12.6% share in 2023. Conversely, the proportion of crashes in 30 mph zones fell from 58.6% in 2023 to 20.3% in 2024. The single fatal crash in 2024 occurred in a 35 mph zone, whereas the fatal crash in the prior year was in a 45 mph zone.

Fatal crashes by zone: 35 mph: 1 of 77 (1.299%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: LOWELL, MA
  • Total crash records analyzed: 2,646
  • Total persons involved: 6,722
  • Total vehicles involved: 5,090

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/2024-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

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Lowell, MA Crash Report — 2024 | ThatCarHitMe.com