ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHARLESTON, VT · 2016
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/vermont/charleston/2016-annual-report
Yearly Traffic Safety Analysis
9 CRASHES IN
CHARLESTON, VT
2016
In 2016, Charleston experienced 9 crashes, a decrease of 30.77% compared to 13 crashes in 2015. Despite the overall decrease in crashes, the number of fatal crashes rose from 0 in 2015 to 1 in 2016, resulting in 1 fatality in 2016 compared to 0 in the prior year. Additionally, DUI-related crashes increased from 0 in 2015 to 1 in 2016.
9
▼ -30.8%was 13
Total Crash Events
1
Fatal Crashes
1
▼ -66.7%was 3
Injury Crashes
1
Fatal Crash Events
Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes in Charleston decreased year-over-year, falling from 13 crashes in 2015 to 9 crashes in 2016. This represents a 30.77% reduction in total crash incidents. Despite this decline, fatal crashes increased from 0 to 1, and DUI crashes also increased from 0 to 1.
When Crashes Happen
The peak day for crashes remained Saturday in both years, though the number of crashes on Saturdays decreased from 4 in 2015 to 3 in 2016. The peak crash hour shifted significantly from 11 PM with 2 crashes in 2015 to 7 AM with 2 crashes in 2016. Crashes occurring at 7 AM increased from 1 in 2015 to 2 in 2016, while crashes at 11 PM decreased from 2 in 2015 to 0 in 2016.
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Crash date field aggregated by weekday
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes shifted notably year-over-year. Fatal crashes increased from 0 in 2015 to 1 in 2016, causing the fatal crash rate to rise from 0% to 11.1% of all crashes. Conversely, injury crashes decreased from 3 in 2015 to 1 in 2016, reducing their proportion from 23.1% to 11.1% of total crashes. Crashes resulting in no injury saw an increase in count from 1 to 4, and their proportion rose from 7.7% to 44.4%.
Outcome by Severity (Crash Events)
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)
Severity Distribution (Crash Events)
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Weather conditions showed a shift, with crashes in clear weather remaining stable at 3 in both years. In 2016, 'Freezing Precipitation' was a factor in 3 crashes, a condition not highlighted in the top conditions for 2015, which instead reported 2 crashes in 'Cloudy' conditions. Crashes occurring in dark conditions decreased from 6 in 2015 to 2 in 2016, while crashes in daylight remained at 7 for both years. Road surface condition data was not available for comparison in 2015.
Weather
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Weather condition at time of crash
Lighting
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Lighting condition field
Road Surface
Source: Vermont Crash Data · Arcgis Open Data · 2016-01-01 to 2016-12-31 · Road surface condition field
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Vermont Crash Data, accessed programmatically via the Arcgis 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 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: 2016-01-01 through 2016-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2016-01-01 through 2016-12-31 (366 days)
- Geographic scope: Charleston, VT
- Total crash records analyzed: 9
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). "Charleston, VT Crash Intelligence Report: 2016." Published July 5, 2026. Reporting period: 2016-01-01 to 2016-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/charleston/2016-annual-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: Vermont Crash Data · Arcgis
Period: 2016-01-01 – 2016-12-31
Generated: July 5, 2026 · All rights reserved