Monthly Traffic Safety Analysis

6 CRASHES IN
BOYLSTON, MA
OCTOBER 2024

All metrics benchmarked againstOctober 2023

Total crashes in October 2024 increased to 6, a 50% rise compared to the 4 crashes reported in October 2023. This period also saw a 100% increase in total injuries, rising from 2 to 4. Conversely, crashes involving DUI decreased from 2 in the prior year to 0 in the current period, representing a 100% reduction.

6

50.0%was 4

Total Crash Events

0

Persons Killed

4

100.0%was 2

Persons Injured

0

Fatal Crash Events

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 · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in October 2024 showed an upward trend compared to the previous year, with total crashes increasing by 50% from 4 to 6. Total injuries also rose significantly, experiencing a 100% increase from 2 to 4. Fatalities remained at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 2100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns show some shifts year-over-year. While Friday remained a peak day for crashes in both periods, the number of crashes on Friday doubled from 1 in October 2023 to 2 in October 2024. The peak hour for crashes shifted from 8p in the prior period to 6p in the current period, both recording 1 crash.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The fatal crash rate remained at 0% for both October 2023 and October 2024. Total injuries increased from 2 to 4 year-over-year. Crashes resulting in 'Minor Injury' decreased in proportion from 50% (2 of 4 crashes) in the prior period to 16.7% (1 of 6 crashes) in the current period, while 'Possible Injury' crashes, absent in the prior period, accounted for 2 crashes (33.3%) in the current period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes16.7%
-50.0%prior 2
Possible Injury2possible injury crashes33.3%
No Injury3no injury crashes50%
50.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving', increased in count from 1 crash in October 2023 to 3 crashes in October 2024. Factors such as 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner', 'Physical impairment', and 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway', each accounting for 1 crash in the prior period, were not observed in the current period. New factors appearing in October 2024, each with 1 crash, include 'Failure to keep in proper lane or running off road' and 'Fatigued/asleep'.

Officer-Reported Primary Contributing Cause

No improper driving3 (50%)
Failure to keep in proper lane or running off road1 (16.7%)
Fatigued/asleep1 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

For lighting conditions, both 'Dark - lighted roadway' and 'Daylight' conditions consistently accounted for 2 crashes in both October 2023 and October 2024. However, the current period introduced 1 crash under 'Dark - roadway not lighted' and 1 crash under 'Dusk', which were not present in the prior period's data. Data for weather and road surface conditions for the prior period is unavailable for comparison.

Weather

Clear5 (83.3%)
Rain1 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway2 (33.3%)
Daylight2 (33.3%)
Dark - roadway not lighted1 (16.7%)
Dusk1 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field

Road Surface

Dry5 (83.3%)
Wet1 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (8 vehicles)

1
BMW1 (12.5%)
2
GMC1 (12.5%)
3
HONDA1 (12.5%)
4
LEXUS1 (12.5%)
5
NISSAN1 (12.5%)
6
SUBARU1 (12.5%)
7
TOYOTA1 (12.5%)
8
VOLKSWAGEN1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records

Sex Distribution (9 persons with recorded sex)

Male6 (66.7%)
20.0%prior 5
Female3 (33.3%)
50.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events

Speed Limit Zones

Fatal rates across all speed zones remained at 0% for both periods. Crashes occurring in 35 mph zones increased from 1 in October 2023 to 2 in October 2024, while crashes in 45 mph zones remained constant at 1. The current period saw 2 crashes in 50 mph zones, a category not present in the prior period, and crashes in 20 mph and 30 mph zones (1 crash each in the prior period) were not observed in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-10-01 through 2024-10-31 (31 days)
  • Geographic scope: BOYLSTON, MA
  • Total crash records analyzed: 6
  • Total persons involved: 9
  • Total vehicles involved: 8

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). "BOYLSTON, MA Crash Intelligence Report: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/boylston/october-2024-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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Boylston, MA Crash Report — October 2024 | ThatCarHitMe.com