Monthly Traffic Safety Analysis

265 CRASHES IN
LOWELL, MA
OCTOBER 2022

All metrics benchmarked againstOctober 2021

Total crashes in Lowell, MA decreased by 5.02% year-over-year, from 279 crashes in October 2021 to 265 crashes in October 2022. The most significant shift was the reduction in total fatalities, which dropped from 1 in October 2021 to 0 in October 2022.

265

-5.0%was 279

Total Crash Events

0

-100.0%was 1

Persons Killed

65

-17.7%was 79

Persons Injured

64

-5.9%was 68

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in Lowell, MA show a slight downward trend year-over-year. The total number of crashes decreased from 279 in October 2021 to 265 in October 2022, representing a 5.02% reduction. This indicates a minor improvement in overall crash frequency.

64

Hit-and-Run Crashes — October 2022

-5.9% vs prior (68)

The number of hit-and-run crashes decreased from 68 in October 2021 to 64 in October 2022. The hit-and-run rate remained relatively stable, decreasing slightly from 24.4% in October 2021 to 24.2% in October 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 1200.0%

3

Cyclists Injured

Prior: 250.0%

58

Motorists Injured

Prior: 76-23.7%

1

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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 in October 2021 (50 crashes) to Sunday in October 2022 (44 crashes). The peak hour also changed, moving from 3 PM in October 2021 (30 crashes) to 6 PM in October 2022 (25 crashes), suggesting a shift in the busiest times for crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities decreased from 1 in October 2021 to 0 in October 2022, and fatal crashes similarly dropped from 1 to 0. Total injuries also saw a reduction, falling from 79 in October 2021 to 65 in October 2022. The proportion of serious injuries remained constant at 1.1% in both periods, while minor injuries increased from a 7.5% share to 8.7% and possible injuries decreased from a 9% share to 7.2%.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1.1%
0.0%prior 3
Minor Injury23minor injury crashes8.7%
9.5%prior 21
Possible Injury19possible injury crashes7.2%
-24.0%prior 25
No Injury177no injury crashes66.8%
14.9%prior 154

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased by 22, from 104 in October 2021 to 82 in October 2022. Conversely, 'Inattention' crashes increased by 14, rising from 17 to 31 year-over-year. 'Failed to yield right of way' saw a minor increase of 2 crashes, from 19 to 21.

Officer-Reported Primary Contributing Cause

No improper driving82 (30.9%)-21.2%prior 104
Inattention31 (11.7%)82.4%prior 17
Failed to yield right of way21 (7.9%)10.5%prior 19
Disregarded traffic signs, signals, road markings10 (3.8%)-23.1%prior 13
Followed too closely8 (3%)-20.0%prior 10
Made an improper turn7 (2.6%)
Failure to keep in proper lane or running off road6 (2.3%)0.0%prior 6
Visibility obstructed5 (1.9%)
Distracted5 (1.9%)
Other improper action5 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes under 'Clear' weather conditions slightly increased from 143 in October 2021 to 149 in October 2022, while crashes under 'Rain' conditions decreased from 35 to 22. Crashes occurring in daylight decreased from 166 in October 2021 to 147 in October 2022. The number of crashes on wet road surfaces decreased from 76 in October 2021 to 57 in October 2022.

Weather

Clear149 (57.8%)
4.2%prior 143
Clear/Clear32 (12.4%)
-23.8%prior 42
Rain22 (8.5%)
-37.1%prior 35
Cloudy17 (6.6%)
112.5%prior 8
Cloudy/Rain10 (3.9%)
-44.4%prior 18
Rain/Rain7 (2.7%)
-50.0%prior 14
Rain/Cloudy6 (2.3%)
Cloudy/Cloudy4 (1.6%)
Clear/Other2 (0.8%)
Clear/Cloudy2 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash

Lighting

Daylight147 (57.2%)
-11.4%prior 166
Dark - lighted roadway92 (35.8%)
2.2%prior 90
Dark - roadway not lighted8 (3.1%)
Dusk4 (1.6%)
-20.0%prior 5
Dawn3 (1.2%)
Other2 (0.8%)
Dark - unknown roadway lighting1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field

Road Surface

Dry199 (77.4%)
4.7%prior 190
Wet57 (22.2%)
-25.0%prior 76
Sand, mud, dirt, oil, gravel1 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 565 in October 2021 to 529 in October 2022. Toyota remained the top make involved in crashes, though its count decreased from 102 to 96, while Honda also saw a decrease from 99 to 91. The 21-25 age group saw an increase in persons involved, from 58 to 68, while the 0-15 age group saw a decrease from 50 to 34.

Top Vehicle Makes (529 vehicles)

1
TOYOTA96 (18.1%)
-5.9%prior 102
2
HONDA91 (17.2%)
-8.1%prior 99
3
FORD40 (7.6%)
-23.1%prior 52
4
NISSAN31 (5.9%)
10.7%prior 28
5
CHEVROLET29 (5.5%)
-12.1%prior 33
6
HYUNDAI20 (3.8%)
66.7%prior 12
7
KIA19 (3.6%)
90.0%prior 10
8
JEEP17 (3.2%)
-15.0%prior 20
9
ACURA14 (2.6%)
0.0%prior 14
10
MERCEDES-BENZ14 (2.6%)
-12.5%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records

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

Sex Distribution (488 persons with recorded sex)

Male267 (54.7%)
-11.6%prior 302
Female220 (45.1%)
-6.8%prior 236
X / Unspecified1 (0.2%)
0.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 3 in October 2021 to 16 in October 2022. Crashes in 30 mph zones slightly decreased from 58 to 54, and crashes in 35 mph zones decreased from 10 to 8. No fatalities were recorded in any specific speed limit zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-10-01 through 2022-10-31 (31 days)
  • Geographic scope: LOWELL, MA
  • Total crash records analyzed: 265
  • Total persons involved: 669
  • Total vehicles involved: 529

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: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/october-2022-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 — October 2022 | ThatCarHitMe.com