ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LOWELL, MA · MAY 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/may-2022-report
Monthly Traffic Safety Analysis
255 CRASHES IN
LOWELL, MA
MAY 2022
In May 2022, Lowell experienced 255 total crashes, an 11.35% increase compared to the 229 crashes recorded in May 2021. The most notable year-over-year shift was a significant 66.67% decrease in total fatalities, from 3 in May 2021 to 1 in May 2022. Total injuries, however, rose by 31.25%, from 64 to 84.
255
▲ 11.4%was 229
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
84
▲ 31.3%was 64
Persons Injured
48
▲ 9.1%was 44
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. 37 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crash frequency, with total crashes rising by 11.35% year-over-year from 229 to 255. Despite this increase in crash volume, total fatalities decreased by 66.67%, from 3 to 1. Concurrently, total injuries increased by 31.25%, from 64 to 84.
48
Hit-and-Run Crashes — May 2022
▲ 9.1% vs prior (44)
The number of hit-and-run crashes increased by 4, from 44 in May 2021 to 48 in May 2022, representing a 9.09% rise in count. Despite this increase in count, the hit-and-run rate slightly decreased from 19.2% in May 2021 to 18.8% in May 2022.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Pedestrians Injured
4
Cyclists Injured
80
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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 with 43 crashes in May 2021 to Wednesday with 41 crashes in May 2022. The peak hour also shifted, with 5 PM recording 21 crashes in May 2021, while 3 PM recorded 27 crashes in May 2022. Overall, crash counts were higher across most days of the week in May 2022 compared to May 2021.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate decreased significantly from 1.31% in May 2021 to 0.39% in May 2022. While fatal crashes decreased from 3 to 1, serious injuries increased from 2 to 3, representing a 50% rise in count. Minor injuries also saw a substantial increase of 68.75%, from 16 to 27, and possible injuries increased by 23.81%, from 21 to 26.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving', increased by 17 crashes, from 74 in May 2021 to 91 in May 2022, a 22.97% rise in count. 'Inattention' increased by 8 crashes (53.33%), from 15 to 23, and 'Failed to yield right of way' increased by 7 crashes (50%), from 14 to 21. 'Followed too closely' saw a slight decrease of 1 crash, from 12 to 11.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Both periods predominantly experienced crashes under 'Clear' weather conditions, with 151 crashes in May 2022 compared to 123 in May 2021. 'Daylight' remained the primary lighting condition for crashes, increasing from 159 to 185 year-over-year. The majority of crashes in both periods occurred on 'Dry' road surfaces, which increased from 198 to 221 crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 15.03%, from 439 in May 2021 to 505 in May 2022. Toyota and Honda remained the top two vehicle makes involved, with Toyota increasing from 75 to 93 (a 24% rise) and Honda from 71 to 87 (a 22.54% rise). The age group 65+ saw a notable increase in persons involved, from 24 to 47, while the 26-34 age group also saw a significant increase from 89 to 113.
Top Vehicle Makes (505 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
136 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (489 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 59 in May 2021 to 55 in May 2022. Notably, fatal crashes within the 30 mph speed zone decreased from 2 in May 2021 to 0 in May 2022. Crashes in the 25 mph speed zone decreased from 6 to 3, while crashes in the 65 mph speed zone increased from 7 to 8.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: LOWELL, MA
- Total crash records analyzed: 255
- Total persons involved: 658
- Total vehicles involved: 505
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: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/lowell/may-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: 2022-05-01 – 2022-05-31
Generated: June 21, 2026 · All rights reserved