Monthly Traffic Safety Analysis

21 CRASHES IN
NORTON, MA
MAY 2024

All metrics benchmarked againstMay 2023

In May 2024, NORTON experienced 21 crashes, marking a 16.7% increase from the 18 crashes recorded in May 2023. Total injuries saw a substantial rise, increasing by 80% from 5 in May 2023 to 9 in May 2024. Fatalities remained at zero in both periods.

21

16.7%was 18

Total Crash Events

0

Persons Killed

9

80.0%was 5

Persons Injured

0

-100.0%was 1

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 · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for NORTON shows an upward trend year-over-year, with total crashes increasing by 16.7% from 18 in May 2023 to 21 in May 2024. This period also saw a significant 80% rise in total injuries, from 5 to 9. Fatalities remained unchanged at zero for both months.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 4125.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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. In May 2024, the peak day for crashes was Friday with 4 incidents, while in May 2023, Monday recorded the highest count with 6 crashes. Similarly, the peak hour for crashes moved from 5 PM with 4 incidents in May 2023 to 4 PM with 3 incidents in May 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both May 2024 and May 2023. Total injuries, however, increased from 5 in May 2023 to 9 in May 2024. The number of serious injuries (severity A) doubled from 1 in May 2023 to 2 in May 2024, while minor (severity B) and possible (severity C) injuries remained constant at 2 each in both periods.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes9.5%
100.0%prior 1
Minor Injury2minor injury crashes9.5%
0.0%prior 2
Possible Injury2possible injury crashes9.5%
0.0%prior 2
No Injury14no injury crashes66.7%
7.7%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' increased by 1 crash from 6 in May 2023 to 7 in May 2024, maintaining its 33.3% share of reported factors. Factors such as 'Followed too closely' and 'Inattention' each increased by 1 crash, rising from 1 to 2 incidents year-over-year. Additionally, 'Failure to keep in proper lane or running off road' was reported in 4 crashes in May 2024, a factor not present in May 2023 data.

Officer-Reported Primary Contributing Cause

No improper driving7 (33.3%)16.7%prior 6
Failure to keep in proper lane or running off road4 (19%)
Followed too closely2 (9.5%)
Inattention2 (9.5%)
Failed to yield right of way2 (9.5%)
Fatigued/asleep1 (4.8%)
Driving too fast for conditions1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Analysis of lighting conditions shows a slight increase in crashes occurring during daylight, rising from 16 in May 2023 to 17 in May 2024. Crashes in 'Dark - lighted roadway' conditions also increased from 1 to 2 incidents. Notably, 'Dark - roadway not lighted' conditions accounted for 1 crash in May 2024, while 'Dusk' conditions, which saw 1 crash in May 2023, had none in May 2024.

Weather

Clear14 (66.7%)
Cloudy3 (14.3%)
Rain3 (14.3%)
Clear/Unknown1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight17 (81.0%)
6.3%prior 16
Dark - lighted roadway2 (9.5%)
Dark - roadway not lighted1 (4.8%)
Dark - unknown roadway lighting1 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry17 (81.0%)
Wet4 (19.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (40 vehicles)

1
TOYOTA8 (20%)
2
FORD4 (10%)
-20.0%prior 5
3
NISSAN4 (10%)
4
GMC4 (10%)
5
HONDA3 (7.5%)
-57.1%prior 7
6
HYUNDAI3 (7.5%)
7
SUBARU3 (7.5%)
8
RAM2 (5%)
9
JEEP2 (5%)
10
VOLVO1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

Sex Distribution (45 persons with recorded sex)

Male26 (57.8%)
-18.8%prior 32
Female19 (42.2%)
5.6%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 9 in May 2023 to 6 in May 2024, while incidents in 25 mph zones also saw a decrease from 2 to 1. Conversely, crashes in 35 mph zones increased from 3 to 5, and 40 mph zones also saw an increase from 3 to 5 incidents. A new crash occurred in a 10 mph zone in May 2024, with no crashes reported in this zone in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: NORTON, MA
  • Total crash records analyzed: 21
  • Total persons involved: 49
  • Total vehicles involved: 40

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). "NORTON, MA Crash Intelligence Report: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norton/may-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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Norton, MA Crash Report — May 2024 | ThatCarHitMe.com