Yearly Traffic Safety Analysis

44 CRASHES IN
TRURO, MA
2024

All metrics benchmarked against2023

In 2024, Truro recorded 44 total crashes, a significant increase from the single crash reported in 2023. This represents a 4300% year-over-year rise in traffic incidents. This increase was accompanied by 14 injuries in 2024, whereas no injuries were reported in the prior year.

44

4300.0%was 1

Total Crash Events

0

Persons Killed

14

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Truro show a substantial year-over-year increase, rising from 1 crash in 2023 to 44 in 2024. This surge included 14 injuries in 2024, compared to zero injuries in the prior year. Despite the increase in crash volume, there were no fatalities recorded in either period.

1

Hit-and-Run Crashes — 2024

2.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

13

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

The temporal patterns of crashes changed significantly between the two periods. In 2024, crashes were most frequent on Fridays (11 incidents) and Mondays (10 incidents), while the single crash in 2023 also occurred on a Friday. The peak time for incidents moved from 8 AM in 2023 to multiple hours in 2024, including 12 PM, 2 PM, 5 PM, and 10 PM, which each saw 5 crashes. While 2023 had only one crash in July, 2024 experienced crashes throughout the year, peaking in June with 8 incidents.

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

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes6.8%
Minor Injury4minor injury crashes9.1%
Possible Injury2possible injury crashes4.5%
No Injury35no injury crashes79.5%

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

Officer-Reported Primary Contributing Cause

No improper driving18 (40.9%)
Inattention5 (11.4%)
Distracted5 (11.4%)
Driving too fast for conditions3 (6.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (4.5%)
Visibility obstructed2 (4.5%)
Fatigued/asleep2 (4.5%)
Wrong side or wrong way1 (2.3%)
Failed to yield right of way1 (2.3%)

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

Weather

Clear32 (72.7%)
Clear/Other4 (9.1%)
Cloudy4 (9.1%)
Cloudy/Other1 (2.3%)
Other1 (2.3%)
Snow1 (2.3%)
Snow/Blowing sand, snow1 (2.3%)

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

Lighting

Daylight31 (70.5%)
Dark - roadway not lighted6 (13.6%)
Dusk3 (6.8%)
Dark - unknown roadway lighting2 (4.5%)
Dark - lighted roadway1 (2.3%)
Dawn1 (2.3%)

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

Road Surface

Dry37 (84.1%)
Wet4 (9.1%)
Snow2 (4.5%)
Ice1 (2.3%)

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 (75 vehicles)

1
TOYOTA9 (12%)
2
HONDA7 (9.3%)
3
CHEVROLET7 (9.3%)
4
JEEP7 (9.3%)
5
HYUNDAI6 (8%)
6
FORD6 (8%)
7
VOLVO5 (6.7%)
8
SUBARU5 (6.7%)
9
RAM4 (5.3%)
10
BMW4 (5.3%)

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

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

Sex Distribution (79 persons with recorded sex)

Male50 (63.3%)
4900.0%prior 1
Female29 (36.7%)
866.7%prior 3

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

In 2024, crashes occurred across a wide range of speed zones, with the highest concentration in 45 MPH zones (17 crashes) and 50 MPH zones (10 crashes). This contrasts with 2023, where the single recorded crash occurred in a 50 MPH zone. The data indicates a shift, with incidents in 2024 becoming most frequent in the 45 MPH zones. 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: TRURO, MA
  • Total crash records analyzed: 44
  • Total persons involved: 90
  • Total vehicles involved: 75

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). "TRURO, 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/truro/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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Truro, MA Crash Report — 2024 | ThatCarHitMe.com