ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHARLTON, MA · JULY 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.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/charlton/july-2022-report
Monthly Traffic Safety Analysis
45 CRASHES IN
CHARLTON, MA
JULY 2022
Total crashes in CHARLTON, MA for July increased from 42 in 2021 to 45 in 2022, representing a 7.1% rise. This period also saw a significant 60% increase in total injuries, rising from 10 to 16 year-over-year. A notable shift occurred in contributing factors, with 'Followed too closely' crashes increasing by 175%.
45
▲ 7.1%was 42
Total Crash Events
0
Persons Killed
16
▲ 60.0%was 10
Persons Injured
2
▲ 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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in CHARLTON, MA for July showed an upward trend year-over-year, with total crashes rising by 7.1% from 42 in July 2021 to 45 in July 2022. This increase was accompanied by a substantial 60% rise in total injuries, from 10 to 16, indicating a worsening outcome despite a smaller increase in total crash count.
2
Hit-and-Run Crashes — July 2022
▲ 100.0% vs prior (1)
Hit-and-run crashes increased from 1 in July 2021 to 2 in July 2022, representing a 100% rise in count. This led to an increase in the hit-and-run rate from 2.4% to 4.4% of all crashes. The trend for hit-and-run incidents is upward year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday in both periods, increasing from 9 crashes in July 2021 to 11 in July 2022. However, the peak hour for crashes shifted from 2 PM in July 2021 to 8 AM in July 2022, with both hours recording 7 crashes. Crashes on Saturday increased by 4, from 6 to 10, and crashes on Wednesday increased by 4, from 4 to 8.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total fatalities remained at zero for both July 2021 and July 2022, there was a significant increase in injury severity. Serious injury crashes rose by 150%, from 2 in July 2021 to 5 in July 2022, and minor injury crashes doubled from 4 to 8. Additionally, July 2022 saw 1 pedestrian injured and 1 cyclist injured, compared to zero in July 2021.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record
Top Contributing Factors
The most significant shifts in contributing factors include a 175% increase in crashes attributed to 'Followed too closely,' rising from 4 in July 2021 to 11 in July 2022. 'Failure to keep in proper lane or running off road' also saw a substantial increase of 250%, from 2 to 7 crashes. Conversely, crashes linked to 'Inattention' decreased by 44.4%, from 9 to 5, and 'Failed to yield right of way' decreased by 40%, from 5 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There was a significant shift towards crashes occurring in clear weather and dry road conditions in July 2022 compared to July 2021. Crashes in clear weather more than doubled, from 21 to 42, while crashes in rainy conditions decreased from 12 to 0. Similarly, crashes on dry road surfaces increased by 19, from 25 to 44, corresponding with a decrease of 16 crashes on wet road surfaces.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 20.8%, from 72 to 87. There was a notable shift in the age distribution of persons involved, with a significant increase of 15 persons in the 45-54 age group (from 8 to 23) and 9 persons in the 26-34 age group (from 17 to 26). Among top vehicle makes, Nissan saw a substantial increase from 1 to 8 vehicles involved, while Toyota decreased from 16 to 12, and Jeep decreased from 7 to 1.
Top Vehicle Makes (87 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records
6 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (96 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 65 mph speed zone increased significantly from 10 in July 2021 to 18 in July 2022, marking an 80% rise. Conversely, crashes in the 55 mph speed zone decreased by 60%, from 5 to 2, and crashes in the 25 mph zone decreased from 3 to 1. All speed zones reported zero fatal crashes in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-07-01 through 2022-07-31 (31 days)
- Geographic scope: CHARLTON, MA
- Total crash records analyzed: 45
- Total persons involved: 104
- Total vehicles involved: 87
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 2022." Published June 21, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/charlton/july-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: 2022-07-01 – 2022-07-31
Generated: June 21, 2026 · All rights reserved