Yearly Traffic Safety Analysis

299 CRASHES IN
SPRINGFIELD, VT
2017

All metrics benchmarked against2016

In 2017, Springfield experienced 299 crashes, marking a 17.25% increase from the 255 crashes recorded in 2016. A significant change was observed in fatal outcomes, with total fatalities increasing by 100% from 1 in the prior year to 2 in the current year. This rise in fatal incidents contributed to a higher fatal crash rate for the period.

299

17.3%was 255

Total Crash Events

2

100.0%was 1

Fatal Crashes

31

-11.4%was 35

Injury Crashes

2

100.0%was 1

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons. 21 crashes with unreported severity are not shown in the severity breakdown.

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Springfield increased year-over-year, rising by 17.25% from 255 crashes in 2016 to 299 crashes in 2017. Despite this increase in total crashes, the number of injuries decreased by 11.43%, from 35 to 31. However, fatal crashes and total fatalities both doubled during this period.

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. The peak day for crashes moved from Friday in 2016, with 48 incidents, to Tuesday in 2017, which recorded 61 crashes. The peak hour for crashes also shifted slightly, from 12 PM with 27 crashes in 2016 to 1 PM with 32 crashes in 2017.

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes showed shifts between the two periods. Fatal crashes increased from 1 in 2016 to 2 in 2017, resulting in a rise in the fatal crash rate from 0.4% to 0.7% of total crashes. Conversely, injury crashes decreased in count from 35 to 31, and their proportion of total crashes fell from 13.7% to 10.4% year-over-year.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.7%
100.0%prior 1
Injury31minor injury crashes10.4%
-11.4%prior 35
No Injury245no injury crashes81.9%
15.0%prior 213

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes under adverse conditions saw some increases year-over-year. Incidents occurring during freezing precipitation rose from 27 in 2016 to 36 in 2017, and crashes on snow-covered roads doubled from 20 to 40. Additionally, crashes occurring in dark conditions increased from 56 to 72, while those in daylight also rose from 193 to 226.

Weather

Clear173 (66.0%)
14.6%prior 151
Cloudy37 (14.1%)
-9.8%prior 41
Freezing Precipitation36 (13.7%)
33.3%prior 27
Rain14 (5.3%)
7.7%prior 13
Wind2 (0.8%)

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Weather condition at time of crash

Lighting

Daylight226 (75.8%)
17.1%prior 193
Dark72 (24.2%)
28.6%prior 56

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Lighting condition field

Road Surface

Dry179 (68.3%)
9.8%prior 163
Snow40 (15.3%)
100.0%prior 20
Wet30 (11.5%)
25.0%prior 24
Ice9 (3.4%)
80.0%prior 5
Slush4 (1.5%)
-42.9%prior 7

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · 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: 2017-01-01 through 2017-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2017-01-01 through 2017-12-31 (365 days)
  • Geographic scope: Springfield, VT
  • Total crash records analyzed: 299

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). "Springfield, VT Crash Intelligence Report: 2017." Published July 5, 2026. Reporting period: 2017-01-01 to 2017-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/springfield/2017-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

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Springfield, VT Crash Report — 2017 | ThatCarHitMe.com