Monthly Traffic Safety Analysis

51 CRASHES IN
CHARLTON, MA
JULY 2024

All metrics benchmarked againstJuly 2023

Total crashes in CHARLTON, MA decreased by 13.56%, from 59 crashes in July 2023 to 51 crashes in July 2024. The most notable shift was a 200% increase in speeding-related crashes, rising from 2 to 6 incidents year-over-year.

51

-13.6%was 59

Total Crash Events

0

Persons Killed

20

-20.0%was 25

Persons Injured

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 · 2024-07-01 to 2024-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in CHARLTON, MA showed a downward trend, decreasing by 13.56% from 59 crashes in July 2023 to 51 crashes in July 2024. Total injuries also decreased from 25 to 20 over the same period. Fatalities remained at 0 in both periods.

1

Hit-and-Run Crashes — July 2024

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 in both July 2023 and July 2024. However, the hit-and-run rate slightly increased from 1.7% to 2% due to a decrease in the total number of crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

20

Motorists Injured

Prior: 25-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In July 2023, Monday was the peak day with 12 crashes, while in July 2024, Sunday became the peak day with 11 crashes. The peak crash hour also shifted from 12 p.m. in July 2023 to 3 p.m. in July 2024, with both hours recording 8 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both July 2023 and July 2024. Serious injuries (A) decreased from 3 to 1, and minor injuries (B) decreased from 14 to 11. However, possible injuries (C) increased from 1 to 3 over the same period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2%
-66.7%prior 3
Minor Injury11minor injury crashes21.6%
-21.4%prior 14
Possible Injury3possible injury crashes5.9%
200.0%prior 1
No Injury35no injury crashes68.6%
-12.5%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Followed too closely' increased from 10 crashes in July 2023 to 13 crashes in July 2024, becoming the most frequent factor. Conversely, 'No improper driving' decreased from 11 crashes to 6 crashes. Speeding-related crashes, as indicated by the KPI, saw a significant increase of 200%, rising from 2 crashes in July 2023 to 6 crashes in July 2024.

Officer-Reported Primary Contributing Cause

Followed too closely13 (25.5%)30.0%prior 10
Inattention10 (19.6%)11.1%prior 9
No improper driving6 (11.8%)-45.5%prior 11
Failed to yield right of way4 (7.8%)
Fatigued/asleep3 (5.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5.9%)
Driving too fast for conditions2 (3.9%)
Visibility obstructed2 (3.9%)
Failure to keep in proper lane or running off road2 (3.9%)
Glare1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 30 in July 2023 to 44 in July 2024, while crashes in rainy conditions decreased from 7 to 2. Similarly, crashes on dry road surfaces increased from 37 to 48, contrasting with a decrease in wet road crashes from 20 to 3. Daylight crashes decreased from 48 to 41, while crashes during dusk increased from 1 to 2.

Weather

Clear44 (88.0%)
46.7%prior 30
Cloudy3 (6.0%)
-57.1%prior 7
Rain2 (4.0%)
-71.4%prior 7
Clear/Cloudy1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Weather condition at time of crash

Lighting

Daylight41 (82.0%)
-14.6%prior 48
Dark - lighted roadway4 (8.0%)
Dark - roadway not lighted3 (6.0%)
-40.0%prior 5
Dusk2 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Lighting condition field

Road Surface

Dry48 (94.1%)
29.7%prior 37
Wet3 (5.9%)
-85.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, Toyota and Ford, both saw decreases in their crash counts, with Toyota dropping from 20 to 12 and Ford from 15 to 10. There was a notable shift in the age distribution of persons involved in crashes, with younger age groups (0-15, 16-20, 21-25, 26-34) showing decreases in counts, while the 35-44 and 55-64 age groups saw increases from 16 to 18 and 8 to 16 respectively.

Top Vehicle Makes (89 vehicles)

1
TOYOTA12 (13.5%)
-40.0%prior 20
2
FORD10 (11.2%)
-33.3%prior 15
3
HONDA8 (9%)
-11.1%prior 9
4
NISSAN7 (7.9%)
-12.5%prior 8
5
AUDI4 (4.5%)
6
HYUNDAI4 (4.5%)
7
CHEVROLET4 (4.5%)
-33.3%prior 6
8
DODGE3 (3.4%)
-40.0%prior 5
9
HD3 (3.4%)
10
VOLVO3 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Vehicle unit records

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

Sex Distribution (103 persons with recorded sex)

Male66 (64.1%)
-8.3%prior 72
Female37 (35.9%)
-27.5%prior 51

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph speed zones more than doubled, increasing from 10 in July 2023 to 22 in July 2024. Conversely, crashes in 40 mph zones decreased from 16 to 6, and in 30 mph zones from 15 to 7. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-07-01 to 2024-07-31 · 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: 2024-07-01 through 2024-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-07-01 through 2024-07-31 (31 days)
  • Geographic scope: CHARLTON, MA
  • Total crash records analyzed: 51
  • Total persons involved: 107
  • Total vehicles involved: 89

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). "CHARLTON, MA Crash Intelligence Report: July 2024." Published June 21, 2026. Reporting period: 2024-07-01 to 2024-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/charlton/july-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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Charlton, MA Crash Report — July 2024 | ThatCarHitMe.com