Yearly Traffic Safety Analysis

4 CRASHES IN
BAKERSFIELD, VT
2017

All metrics benchmarked against2016

Total crashes in Bakersfield, VT decreased significantly from 9 in 2016 to 4 in 2017, representing a 55.6% reduction year-over-year. The most notable shift was the substantial decrease in overall crash incidents. Fatalities remained at zero for both periods.

4

-55.6%was 9

Total Crash Events

0

Fatal Crashes

1

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. 4 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, crash incidents in Bakersfield, VT showed a significant downward trend year-over-year. The total number of crashes decreased by 55.6%, from 9 crashes in 2016 to 4 crashes in 2017. This indicates a substantial improvement in traffic safety during the period.

When Crashes Happen

The peak day for crashes shifted from Tuesday in 2016 to Sunday in 2017, with 2 crashes on each respective peak day. Similarly, the peak hour for crashes moved from 4 p.m. in 2016 to 6 p.m. in 2017, with 2 crashes occurring at each peak time. Crashes in 2017 were concentrated in the later months of the year, specifically March, November, and December, whereas 2016 saw incidents spread across more months including February, June, July, August, and December.

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)

Road & Environmental Conditions

Regarding lighting conditions, there was a notable shift from 2016 to 2017. In 2016, 89% of crashes (8 out of 9) occurred during daylight, while in 2017, 75% of crashes (3 out of 4) occurred in dark conditions. Data for weather and road surface conditions were not available for comparison.

Lighting

Dark3 (75.0%)
Daylight1 (25.0%)
-87.5%prior 8

Source: Vermont Crash Data · Arcgis Open Data · 2017-01-01 to 2017-12-31 · Lighting 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: Bakersfield, VT
  • Total crash records analyzed: 4

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). "Bakersfield, 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/bakersfield/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

ThatCarHitMe.com · An Injuria.ai Company

Bakersfield, VT Crash Report — 2017 | ThatCarHitMe.com