ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LOWELL, MA · 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/2022-annual-report
Yearly Traffic Safety Analysis
2,890 CRASHES IN
LOWELL, MA
2022
In Lowell, total traffic crashes increased by 9.1% from 2,650 in 2021 to 2,890 in 2022. While the number of fatalities remained unchanged at 8 for both years, the number of people injured in crashes saw a significant year-over-year increase. Total injuries rose by 21.2%, from 697 in 2021 to 845 in 2022.
2,890
▲ 9.1%was 2,650
Total Crash Events
8
Persons Killed
845
▲ 21.2%was 697
Persons Injured
638
▲ 8.0%was 591
Hit-and-Run Crashes
Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 502 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 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Lowell show an increase in crash frequency and severity, excluding fatalities. Total crashes rose by 9.1% from 2,650 in 2021 to 2,890 in 2022. This was accompanied by a 21.2% increase in total injuries (from 697 to 845), while total fatalities held steady at 8 in both periods.
638
Hit-and-Run Crashes — 2022
▲ 8.0% vs prior (591)
The total number of hit-and-run crashes increased by 8.0%, from 591 incidents in 2021 to 638 in 2022. Despite this increase in absolute numbers, the hit-and-run rate as a percentage of all crashes remained stable, slightly decreasing from 22.3% to 22.1%. This indicates that the growth in hit-and-run crashes was proportional to the overall increase in total crashes.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
5
Motorists Killed
0
Other Killed
28
Pedestrians Injured
18
Cyclists Injured
796
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Wednesday in 2021 (430 incidents) to Friday in 2022 (451 incidents). The peak hour for collisions remained consistent at 3 p.m. for both years, though the volume of crashes during that hour increased from 215 to 259.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity showed a rise in injury-related incidents from 2021 to 2022. The number and proportion of fatal crashes remained constant at 8 incidents (0.3% of total crashes) in both years. However, the total count of crashes involving any injury (Serious, Minor, or Possible) increased from 478 to 554, raising their share of all crashes from 18.0% in 2021 to 19.2% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors for crashes remained consistent, though their counts increased year-over-year. "Inattention" and "Failed to yield right of way" were the second and third most common factors in both periods, following crashes with no improper driving cited. The count of crashes involving inattention grew by 20.4% (from 191 to 230), while those related to failing to yield increased by 22.0% (from 177 to 216). Crashes citing "Distracted" as a factor saw a 45.7% increase in count, from 35 to 51 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While most crashes in both years occurred in daylight on dry roads, there was a significant increase in crashes under adverse road conditions. The number of incidents occurring on roads with snow or ice more than doubled, rising from a combined 87 crashes in 2021 to 179 in 2022. This raised the share of crashes on snowy or icy surfaces from 3.3% of all incidents in 2021 to 6.2% in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The profile of vehicles and persons involved in crashes was stable between 2021 and 2022. The top three vehicle makes involved in incidents were identical in both years: Honda, Toyota, and Ford, with each seeing an increase in total count. The age distribution of all persons involved in crashes also showed no significant proportional shifts, with age groups like '26-34' (15.4% in 2021 vs. 15.8% in 2022) and '65+' (5.9% in 2021 vs. 5.6% in 2022) maintaining a consistent share of the total.
Top Vehicle Makes (5,749 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
1,679 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (5,542 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones remained consistent, with about 79% of incidents in both 2021 and 2022 occurring in zones posted at 30 mph or less. Crashes in high-speed zones (55 mph or greater) represented 11.1% of the total in 2022, down slightly from a 12.1% share in 2021. In both years, three fatal crashes with recorded speed limits occurred in 30 mph zones. In 2022, an additional fatal crash occurred in a 55 mph zone, whereas 2021 recorded fatal crashes in 35 mph and 65 mph zones.
Fatal crashes by zone: 30 mph: 3 of 562 (0.534%) · 55 mph: 1 of 24 (4.167%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: LOWELL, MA
- Total crash records analyzed: 2,890
- Total persons involved: 7,491
- Total vehicles involved: 5,749
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/2022-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
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 – 2022-12-31
Generated: June 21, 2026 · All rights reserved