ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WATERBURY, VT · 2018
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/waterbury/2018-annual-report
Yearly Traffic Safety Analysis
69 CRASHES IN
WATERBURY, VT
2018
Waterbury experienced a substantial decrease in total crashes, falling by 46.51% from 129 crashes in 2017 to 69 crashes in 2018. Despite this overall reduction, the number of total injuries increased by 75%, from 12 in 2017 to 21 in 2018. Additionally, DUI-related crashes doubled, rising from 3 in the prior year to 6 in the current year. Pedestrian crashes also increased from 0 in 2017 to 3 in 2018.
69
▼ -46.5%was 129
Total Crash Events
0
Fatal Crashes
21
▲ 75.0%was 12
Injury Crashes
0
Fatal Crash Events
Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 20 crashes with unreported severity are not shown in the severity breakdown.
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend for crashes in Waterbury indicates a significant decrease in total incidents, with crashes falling by 46.51% year-over-year. However, this reduction in crash volume was accompanied by a notable increase in total injuries, which rose by 75% during the same period. Fatalities remained at zero in both years.
When Crashes Happen
Temporal patterns shifted year-over-year, with the peak day for crashes moving from Friday and Saturday in 2017 to solely Friday in 2018. The peak hour for crashes also changed, occurring at 2p with 11 crashes in 2017, but shifting to 5p with 8 crashes in 2018. A notable change was observed in December, where crashes decreased sharply from 27 in 2017 to just 3 in 2018.
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Crash date field aggregated by weekday
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The distribution of crash severity saw a significant shift, with injury crashes increasing by 75% from 12 in 2017 to 21 in 2018. This also resulted in injury crashes comprising a larger proportion of total incidents, rising from 9.3% to 30.4% year-over-year. Fatal crashes remained at zero in both periods.
Outcome by Severity (Crash Events)
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)
Severity Distribution (Crash Events)
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions saw several changes, with crashes occurring in clear weather increasing from 16 in 2017 to 26 in 2018. Incidents during freezing precipitation decreased from 9 to 4, while rain-related crashes rose from 1 to 6. Crashes on dry road surfaces increased from 17 to 35, while those on wet, snow, or ice-covered surfaces generally decreased in count.
Weather
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Weather condition at time of crash
Lighting
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · Lighting condition field
Road Surface
Source: Vermont Crash Data · Arcgis Open Data · 2018-01-01 to 2018-12-31 · 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: 2018-01-01 through 2018-12-31
- Report generated: July 5, 2026
Data Coverage
- Reporting period: 2018-01-01 through 2018-12-31 (365 days)
- Geographic scope: Waterbury, VT
- Total crash records analyzed: 69
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). "Waterbury, VT Crash Intelligence Report: 2018." Published July 5, 2026. Reporting period: 2018-01-01 to 2018-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/waterbury/2018-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: 2018-01-01 – 2018-12-31
Generated: July 5, 2026 · All rights reserved