Yearly Traffic Safety Analysis

15 CRASHES IN
CHILMARK, MA
2024

All metrics benchmarked against2023

In Chilmark, total crashes increased by 87.5% from 8 in 2023 to 15 in 2024. This increase was accompanied by a rise in total injuries from 3 to 5, while fatalities remained at zero in both periods. The most significant year-over-year shift was the emergence of DUI-related crashes, which increased from zero in the prior year to 3 in the current year, accounting for 20% of all 2024 collisions.

15

87.5%was 8

Total Crash Events

0

Persons Killed

5

66.7%was 3

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Chilmark showed a significant upward trend year-over-year, with the total number of incidents rising 87.5% from 8 to 15. The number of people injured in these crashes also increased by 66.7%, from 3 to 5. However, there were no fatalities reported in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. The day with the most crashes changed from Saturday in 2023 to Monday in 2024, which recorded 4 incidents. The peak hour for crashes also moved significantly, from various single-crash hours in the prior year to 1 a.m. in the current year, which accounted for 3 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of injuries increased from 3 to 5 year-over-year, the reported severity of those injuries was lower in the current period. In 2023, one crash was categorized as resulting in a 'Serious Injury,' representing 12.5% of that year's total. In 2024, there were no serious injury crashes; instead, crashes with injuries were classified as 'Minor Injury' (2 crashes) and 'Possible Injury' (1 crash).

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes13.3%
Possible Injury1possible injury crashes6.7%
No Injury9no injury crashes60%
28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors cited in crashes shifted between the two years. In 2024, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased in count from 1 to 3 incidents. In contrast, 'Inattention,' which was the top factor in 2023 with 2 crashes, decreased to 1 crash in 2024. Speeding-related factors, including 'Exceeded authorized speed limit,' were associated with 5 crashes in 2024, up from 1 in 2023.

Officer-Reported Primary Contributing Cause

No improper driving7 (46.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (20%)
Exceeded authorized speed limit2 (13.3%)
Driving too fast for conditions1 (6.7%)
Inattention1 (6.7%)
Other improper action1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While the proportion of crashes in clear weather and on dry roads remained consistent at approximately 87% in both years, there was a notable change in lighting conditions. The share of crashes occurring in daylight decreased from 62.5% (5 of 8 crashes) in 2023 to 40% (6 of 15 crashes) in 2024. Correspondingly, crashes in dark or dawn conditions rose from 37.5% of the total in the prior year to 60% in the current year.

Weather

Clear/Clear9 (60.0%)
Clear3 (20.0%)
Clear/Cloudy1 (6.7%)
Rain1 (6.7%)
Rain/Rain1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted7 (46.7%)
Daylight6 (40.0%)
20.0%prior 5
Dawn2 (13.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry13 (86.7%)
85.7%prior 7
Wet2 (13.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (17 vehicles)

1
FORD3 (17.6%)
2
TOYOTA3 (17.6%)
3
HONDA2 (11.8%)
4
AUDI2 (11.8%)
5
MAZDA2 (11.8%)
6
SUBARU1 (5.9%)
7
CHEVROLET1 (5.9%)
8
NISSAN1 (5.9%)
9
FRHT1 (5.9%)
10
GMC1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

Sex Distribution (18 persons with recorded sex)

Male15 (83.3%)
150.0%prior 6
Female3 (16.7%)
-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 35 mph speed zone was the most frequent location for crashes in both periods, and its incident count more than doubled from 4 crashes in 2023 to 9 in 2024. The number of crashes in the 30 mph zone remained stable at 2 incidents for both years. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: CHILMARK, MA
  • Total crash records analyzed: 15
  • Total persons involved: 18
  • Total vehicles involved: 17

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). "CHILMARK, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chilmark/2024-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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Chilmark, MA Crash Report — 2024 | ThatCarHitMe.com