Monthly Traffic Safety Analysis

13 CRASHES IN
NORTH READING, MA
FEBRUARY 2022

All metrics benchmarked againstFebruary 2021

Total crashes in NORTH READING remained stable year-over-year, with 13 crashes reported in February 2022, mirroring the 13 crashes in February 2021. However, the current period saw a significant shift with the occurrence of 1 fatal crash and 1 fatality, compared to no fatal crashes or fatalities in the prior period. Total injuries decreased substantially from 7 in February 2021 to 2 in February 2022.

13

Total Crash Events

1

Persons Killed

2

-71.4%was 7

Persons Injured

1

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. 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

Overall crash volume remained stable year-over-year, with 13 crashes recorded in both February 2022 and February 2021. While total injuries decreased from 7 to 2, the current period marked a concerning emergence of 1 fatal crash and 1 fatality, which were absent in the prior year.

1

Hit-and-Run Crashes — February 2022

7.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Cyclists Injured

Prior: 0%

1

Motorists Injured

Prior: 7-85.7%

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 peak day for crashes shifted from Thursday (4 crashes) in the prior period to Friday (3 crashes) in the current period, indicating a change in weekly crash distribution. Similarly, the peak crash hour moved from 2 PM (4 crashes) in the prior period to 8 PM (2 crashes) in the current period, suggesting a later concentration of incidents.

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

Fatal crashes increased from 0 in February 2021 to 1 in February 2022, representing 7.7% of total crashes in the current period. Total injuries saw a notable decrease from 7 persons injured in the prior period to 2 persons injured in the current period. Specifically, possible injury crashes (severity C) decreased from 4 to 1.

Outcome by Severity (Crash Events)

Fatal1fatal crashes7.7%
Minor Injury1minor injury crashes7.7%
Possible Injury1possible injury crashes7.7%
-75.0%prior 4
No Injury9no injury crashes69.2%
0.0%prior 9

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

Crashes attributed to "Failed to yield right of way" decreased by 4, from 6 in the prior period to 2 in the current period, and "No improper driving" crashes decreased by 2, from 5 to 3. Conversely, factors such as "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner," "Driving too fast for conditions," "Physical impairment," and "Illness" each appeared once in the current period, having not been present in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving3 (23.1%)-40.0%prior 5
Failed to yield right of way2 (15.4%)-66.7%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (7.7%)
Other improper action1 (7.7%)
Over-correcting/over-steering1 (7.7%)
Physical impairment1 (7.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (7.7%)
Driving too fast for conditions1 (7.7%)
Illness1 (7.7%)

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

The number of crashes occurring in "Clear" weather remained consistent at 9 for both periods. Crashes during "Daylight" conditions decreased from 12 in the prior period to 9 in the current period, while those in "Dark - lighted roadway" increased from 1 to 4. Crashes on "Dry" road surfaces increased from 6 to 8, contrasting with a decrease in "Wet" road surface crashes from 6 to 2.

Weather

Clear9 (69.2%)
0.0%prior 9
Clear/Other1 (7.7%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (7.7%)
Sleet, hail (freezing rain or drizzle)/Snow1 (7.7%)
Snow/Cloudy1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash

Lighting

Daylight9 (69.2%)
-25.0%prior 12
Dark - lighted roadway4 (30.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field

Road Surface

Dry8 (61.5%)
33.3%prior 6
Wet2 (15.4%)
-66.7%prior 6
Ice1 (7.7%)
Slush1 (7.7%)
Snow1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (19 vehicles)

1
FORD4 (21.1%)
2
TOYOTA4 (21.1%)
3
HONDA3 (15.8%)
4
JEEP2 (10.5%)
5
NISSAN2 (10.5%)
6
SUBARU1 (5.3%)
7
HYUNDAI1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records

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

Sex Distribution (20 persons with recorded sex)

Female10 (50.0%)
-16.7%prior 12
Male10 (50.0%)
-37.5%prior 16

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 within the 30 MPH speed limit zone saw a significant increase from 3 in the prior period to 9 in the current period, which included the only fatal crash. In contrast, crashes in the 40 MPH speed limit zone decreased from 6 to 1, and those in the 10 MPH zone decreased from 2 to 1.

Fatal crashes by zone: 30 mph: 1 of 9 (11.111%)

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 READING, MA
  • Total crash records analyzed: 13
  • Total persons involved: 22
  • Total vehicles involved: 19

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 READING, 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-reading/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

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North Reading, MA Crash Report — February 2022 | ThatCarHitMe.com