ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORTH ANDOVER, MA · FEBRUARY 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.
Monthly Traffic Safety Analysis
47 CRASHES IN
NORTH ANDOVER, MA
FEBRUARY 2022
In February 2022, NORTH ANDOVER experienced 47 crashes, a notable increase from the 30 crashes recorded in February 2021, representing a 56.7% rise. A significant shift was observed in DUI-related crashes, which increased from 0 in the prior period to 3 in the current period. Total injuries also saw an increase, rising from 5 to 6 year-over-year.
47
▲ 56.7%was 30
Total Crash Events
0
Persons Killed
6
▲ 20.0%was 5
Persons Injured
1
▼ -50.0%was 2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a substantial increase in crash incidents in NORTH ANDOVER, with total crashes rising by 56.7% from 30 in February 2021 to 47 in February 2022. Concurrently, total injuries increased by 20%, from 5 to 6, suggesting a worsening safety trend year-over-year.
1
Hit-and-Run Crashes — February 2022
▼ -50.0% vs prior (2)
Hit-and-run crashes decreased by 50% year-over-year, falling from 2 incidents in February 2021 to 1 incident in February 2022. Consequently, the hit-and-run rate also decreased, from 6.7% in the prior period to 2.1% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns shifted year-over-year; the peak day for crashes moved from Friday with 8 crashes in February 2021 to Thursday with 9 crashes in February 2022. The peak hour remained 4p-5p, with 6 crashes occurring at 4p in the prior period and 6 crashes at 5p in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at 0 in both periods, indicating no change in the fatal crash rate. The number of crashes resulting in any injury increased from 3 in February 2021 to 5 in February 2022. While minor injuries increased from 1 to 3 crashes, serious injuries appeared in the current period with 1 crash, compared to none in the prior period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving', saw a significant increase in count from 8 in February 2021 to 22 in February 2022. 'Failed to yield right of way' crashes decreased substantially from 8 to 1, while 'Inattention' crashes increased from 5 to 7. Additionally, 'Driving too fast for conditions' crashes, which were 0 in the prior period, accounted for 3 crashes in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes under 'Clear' weather conditions increased from 18 to 29, and those under 'Rain' increased from 1 to 7. Conversely, crashes during 'Snow' conditions decreased from 7 to 2. Regarding road surface, crashes on 'Dry' roads increased from 16 to 23, and those on 'Wet' roads increased from 7 to 11, while crashes on 'Ice' surfaces appeared in the current period with 4 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 55.6%, from 54 in February 2021 to 84 in February 2022. Honda and Toyota remained the top two vehicle makes involved, with Honda increasing from 11 to 16 and Toyota from 9 to 14. All age groups saw an increase in person counts, with the 26-34 age group experiencing the largest increase from 9 to 20 persons.
Top Vehicle Makes (84 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (81 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 40 mph speed zone saw the largest increase, rising from 7 in February 2021 to 15 in February 2022. Crashes in the 35 mph zone also increased from 5 to 9, and the 15 mph zone from 1 to 4. Conversely, crashes in the 45 mph zone decreased from 3 to 1, and the 65 mph zone, present in the prior period, had no crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-02-01 through 2022-02-28 (28 days)
- Geographic scope: NORTH ANDOVER, MA
- Total crash records analyzed: 47
- Total persons involved: 91
- Total vehicles involved: 84
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). "NORTH ANDOVER, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-andover/february-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: 2022-02-01 – 2022-02-28
Generated: June 21, 2026 · All rights reserved