Monthly Traffic Safety Analysis

20 CRASHES IN
BOLTON, MA
DECEMBER 2022

All metrics benchmarked againstDecember 2021

In December 2022, Bolton recorded 20 total crashes, which is consistent with the 20 crashes reported in December 2021, representing a 0% change year-over-year. The most notable shift was the absence of fatalities in the current period, compared to one fatality in the prior year.

20

Total Crash Events

0

-100.0%was 1

Persons Killed

5

25.0%was 4

Persons Injured

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 · 2022-12-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume remained stable year-over-year, with 20 crashes reported in both periods. While total injuries increased from 4 to 5, the most significant change was the decrease in fatalities from 1 in the prior period to 0 in the current period.

1

Hit-and-Run Crashes — December 2022

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 in both the current and prior periods. Consequently, the hit-and-run rate also remained unchanged at 5% for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

5

Motorists Injured

Prior: 366.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In the current period, peak crash activity occurred on Fridays and Saturdays with 5 crashes each, and the peak hour was 6 p.m. with 4 crashes. This contrasts with the prior period, where Wednesday was the peak day with 7 crashes and 4 p.m. was the peak hour with 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity showed a positive trend, with no fatal crashes reported in the current period compared to one fatal crash in the prior period, reducing the fatal crash rate from 5% to 0%. Minor injury crashes remained constant at 3 incidents in both periods, accounting for 15% of crashes in the current period and 15% in the prior period.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes15%
0.0%prior 3
No Injury17no injury crashes85%
6.3%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Among common contributing factors, 'No improper driving' crashes increased from 7 in the prior period to 8 in the current period, a 14.3% increase. Crashes attributed to 'Distracted' driving decreased by 50%, from 2 in the prior period to 1 in the current period. 'Failed to yield right of way' was a factor in 4 crashes in the current period, but was not explicitly listed as a factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving8 (40%)14.3%prior 7
Failed to yield right of way4 (20%)
Failure to keep in proper lane or running off road2 (10%)
Other improper action1 (5%)
Over-correcting/over-steering1 (5%)
Distracted1 (5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5%)
Inattention1 (5%)
Made an improper turn1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under adverse weather conditions, including rain or snow, increased from 1 in the prior period to 5 in the current period. Crashes in dark conditions (roadway not lighted or lighted) rose from 8 in the prior period to 13 in the current period. Incidents on wet road surfaces increased from 4 to 6 crashes year-over-year.

Weather

Clear11 (57.9%)
-15.4%prior 13
Cloudy3 (15.8%)
-50.0%prior 6
Rain2 (10.5%)
Snow1 (5.3%)
Cloudy/Snow1 (5.3%)
Cloudy/Rain1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted10 (50.0%)
Daylight4 (20.0%)
-50.0%prior 8
Dark - lighted roadway3 (15.0%)
Dawn2 (10.0%)
Dusk1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry13 (65.0%)
-13.3%prior 15
Wet6 (30.0%)
Snow1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (40 vehicles)

1
FORD9 (22.5%)
2
TOYOTA5 (12.5%)
3
SUBARU4 (10%)
4
CHEVROLET4 (10%)
-33.3%prior 6
5
FREIGHTLINER2 (5%)
6
KIA1 (2.5%)
7
LEXUS1 (2.5%)
8
MAZDA1 (2.5%)
9
MERCEDES-BENZ1 (2.5%)
10
PETERBILT1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Vehicle unit records

3 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (40 persons with recorded sex)

Male31 (77.5%)
82.4%prior 17
Female9 (22.5%)
-55.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

There was a notable shift in crash distribution across speed zones. Crashes in 30 mph zones increased from 2 to 5 (a 150% increase), and those in 65 mph zones increased from 3 to 8 (a 166.7% increase). Conversely, crashes in 40 mph zones decreased from 7 to 3, and in 45 mph zones from 6 to 3. No fatalities were recorded in any speed zone in the current period, whereas the prior period saw one fatal crash in a 35 mph zone.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-12-01 to 2022-12-31 · 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: 2022-12-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-12-01 through 2022-12-31 (31 days)
  • Geographic scope: BOLTON, MA
  • Total crash records analyzed: 20
  • Total persons involved: 45
  • Total vehicles involved: 40

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). "BOLTON, MA Crash Intelligence Report: December 2022." Published June 21, 2026. Reporting period: 2022-12-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bolton/december-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

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Bolton, MA Crash Report — December 2022 | ThatCarHitMe.com