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An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LOWELL, MA · JANUARY 2022
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/january-2022-report
Monthly Traffic Safety Analysis
254 CRASHES IN
LOWELL, MA
JANUARY 2022
In January 2022, Lowell experienced 254 crashes, a substantial increase compared to the 176 crashes recorded in January 2021, representing a 44.3% rise. A notable shift is the occurrence of 1 fatality in the current period, compared to 0 fatalities in the prior year.
254
▲ 44.3%was 176
Total Crash Events
1
Persons Killed
59
▲ 55.3%was 38
Persons Injured
43
▲ 10.3%was 39
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. 54 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Lowell show a significant upward trend year-over-year, increasing from 176 crashes in January 2021 to 254 crashes in January 2022. This represents a 44.3% increase in total crashes for the month.
43
Hit-and-Run Crashes — January 2022
▲ 10.3% vs prior (39)
The number of hit-and-run crashes increased from 39 in January 2021 to 43 in January 2022. However, the hit-and-run rate decreased from 22.2% of all crashes in the prior period to 16.9% in the current period, indicating a downward trend in the proportion of crashes that are hit-and-runs.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
57
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes show a shift in peak activity. In January 2022, the peak day for crashes was Monday with 45 incidents, moving from Tuesday with 32 incidents in January 2021. The peak hour also shifted from 6 PM with 16 crashes in January 2021 to 2 PM with 23 crashes in January 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes saw a significant change, with 1 fatal crash occurring in January 2022 compared to 0 in January 2021, resulting in a fatal crash rate of 0.39%. Total injuries also increased from 38 to 59. The proportion of crashes resulting in minor injuries rose from 5.7% to 6.7%, while possible injury crashes remained relatively stable, moving from 9.7% to 9.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' increased significantly from 61 crashes in January 2021 to 104 crashes in January 2022, an increase of 43 incidents. 'Failed to yield right of way' more than doubled, rising from 7 to 16 crashes, while 'Inattention' decreased from 20 to 11 crashes. These shifts resulted in 'Failed to yield right of way' becoming the second most frequent factor, replacing 'Inattention'.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on dry road surfaces decreased proportionally from 71% in January 2021 to 58.7% in January 2022, despite an increase in absolute count from 125 to 149. Concurrently, crashes on snow-covered roads saw a proportional increase from 10.2% to 17.7%, and crashes on icy roads significantly increased from 3 incidents (1.7%) to 17 incidents (6.7%). The number of crashes during daylight hours increased from 84 to 145, and during dark-lighted roadway conditions from 73 to 85.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 430 to 645 year-over-year. Notable shifts in age distribution include a rise in persons aged 26-34 (from 76 to 95), 35-44 (from 58 to 89), and 65+ (from 19 to 44). The top three vehicle makes involved in crashes, Honda, Toyota, and Ford, maintained their ranking and all saw an increase in the number of incidents.
Top Vehicle Makes (498 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records
151 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (476 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph speed zones saw a slight increase from 46 incidents in January 2021 to 48 incidents in January 2022. Significantly, this speed zone recorded 1 fatal crash in the current period, leading to a 2.083% fatal rate within this zone, compared to 0 fatal crashes in the prior period.
Fatal crashes by zone: 30 mph: 1 of 48 (2.083%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-01-31 (31 days)
- Geographic scope: LOWELL, MA
- Total crash records analyzed: 254
- Total persons involved: 645
- Total vehicles involved: 498
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: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/january-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-01-31
Generated: June 21, 2026 · All rights reserved