Monthly Traffic Safety Analysis

14 CRASHES IN
NORTH READING, MA
JUNE 2024

All metrics benchmarked againstJune 2023

In June 2024, NORTH READING, MA recorded 14 total crashes, a 17.65% decrease compared to the 17 crashes reported in June 2023. The most notable shift was a significant reduction in crashes attributed to "Failed to yield right of way," which dropped from 8 incidents in the prior period to 2 in the current period. This change coincided with an increase in crashes where "No improper driving" was cited, rising from 2 to 5 incidents.

14

-17.6%was 17

Total Crash Events

0

Persons Killed

2

-60.0%was 5

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend indicates a decrease in crash activity year-over-year in NORTH READING. Total crashes fell by 3 incidents, representing a 17.65% reduction from 17 crashes in June 2023 to 14 crashes in June 2024. Concurrently, total injuries decreased by 60%, from 5 injuries in the prior period to 2 injuries in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 5-60.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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 year-over-year. In June 2023, the peak day for crashes was Thursday with 6 incidents, whereas in June 2024, the peak days were Sunday and Tuesday, each with 4 crashes. The peak hour remained consistent at 4 PM in both periods, with 3 crashes in June 2023 and 4 crashes in June 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both June 2023 and June 2024. Total injuries decreased from 5 in the prior period to 2 in the current period. The severity distribution also changed, with June 2024 recording 1 serious injury (7.1% share) and 1 minor injury (7.1% share), compared to June 2023 which had 2 minor injuries (11.8% share) and 2 possible injuries (11.8% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.1%
Minor Injury1minor injury crashes7.1%
-50.0%prior 2
No Injury12no injury crashes85.7%
-7.7%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

The distribution of contributing factors saw notable changes year-over-year. Crashes attributed to "Failed to yield right of way" decreased significantly by 6 incidents, from 8 in June 2023 to 2 in June 2024. Conversely, crashes where "No improper driving" was cited increased by 3 incidents, from 2 in the prior period to 5 in the current period. "Exceeded authorized speed limit" appeared as a factor in 1 crash in June 2024, while it was not reported in June 2023.

Officer-Reported Primary Contributing Cause

No improper driving5 (35.7%)
Failed to yield right of way2 (14.3%)-75.0%prior 8
Exceeded authorized speed limit1 (7.1%)
Other improper action1 (7.1%)
Made an improper turn1 (7.1%)
Followed too closely1 (7.1%)
Inattention1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained predominantly clear, dry, and daylight in both periods. In June 2024, 13 out of 14 crashes occurred in clear weather, 13 on dry road surfaces, and 13 in daylight. This is comparable to June 2023, where 12 out of 17 crashes occurred in clear weather, 15 on dry road surfaces, and 15 in daylight, indicating no significant shift towards adverse conditions as a dominant factor.

Weather

Clear13 (92.9%)
8.3%prior 12
Cloudy1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight13 (92.9%)
-13.3%prior 15
Dusk1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry13 (92.9%)
-13.3%prior 15
Wet1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (23 vehicles)

1
HONDA5 (21.7%)
2
FORD3 (13%)
3
TOYOTA3 (13%)
-50.0%prior 6
4
JEEP2 (8.7%)
5
CHEVROLET2 (8.7%)
6
DODGE2 (8.7%)
7
VOLVO1 (4.3%)
8
BMW1 (4.3%)
9
NISSAN1 (4.3%)
10
SUBARU1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

Sex Distribution (26 persons with recorded sex)

Female15 (57.7%)
0.0%prior 15
Male11 (42.3%)
-45.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes continued to be most frequent in the 40 mph speed zone in both periods, with 9 crashes in June 2023 and 8 crashes in June 2024. Crashes in the 35 mph zone decreased from 5 to 2, while crashes in the 30 mph zone increased from 2 to 3. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: NORTH READING, MA
  • Total crash records analyzed: 14
  • Total persons involved: 26
  • Total vehicles involved: 23

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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-reading/june-2024-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 — June 2024 | ThatCarHitMe.com