ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BARNSTABLE, MA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/barnstable/2024-annual-report
Yearly Traffic Safety Analysis
1,240 CRASHES IN
BARNSTABLE, MA
2024
In 2024, Barnstable recorded 1,240 traffic crashes, a 1.0% decrease from the 1,253 crashes reported in 2023. While overall crashes and injuries declined, the number of pedestrians injured increased by 62.5%, rising from 8 in the prior period to 13 in the current period.
1,240
▼ -1.0%was 1,253
Total Crash Events
4
Persons Killed
418
▼ -8.7%was 458
Persons Injured
58
▼ -13.4%was 67
Hit-and-Run Crashes
Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 29 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
Overall traffic crashes in Barnstable showed a slight decline, decreasing by 1.0% from 1,253 in 2023 to 1,240 in 2024. This downward trend was also reflected in total injuries, which fell by 8.7% from 458 to 418. The number of fatalities remained unchanged at 4 for both periods.
58
Hit-and-Run Crashes — 2024
▼ -13.4% vs prior (67)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes fell by 13.4%, from 67 in 2023 to 58 in 2024. Consequently, the hit-and-run rate dropped from 5.3% of all crashes in the prior period to 4.7% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
0
Other Killed
13
Pedestrians Injured
13
Cyclists Injured
390
Motorists Injured
2
Other Injured
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 remained largely consistent year-over-year, with Tuesday being the peak day for crashes in both 2024 (200 crashes) and 2023 (203 crashes). However, the peak hour for collisions shifted one hour later, from 4 PM in the prior year (118 crashes) to 5 PM in the current year (111 crashes). Crash counts on Fridays saw a 16.7% increase from 168 to 196 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
Crash severity saw minimal change year-over-year, with the number of fatal crashes holding steady at 4 for both periods, representing 0.3% of all crashes in each year. The proportion of crashes resulting in serious injury also remained unchanged at 2.1%. There was a shift within non-serious injury categories, as crashes classified with 'Minor Injury' decreased from 17.3% to 15.6% of the total, while 'Possible Injury' crashes increased from 6.4% to 7.5%.
Outcome by Severity (Crash Events)
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 leading contributing factors remained consistent, with 'Inattention' and 'Failed to yield right of way' being the top improper driving actions after 'No improper driving' in both years. The count of crashes attributed to 'Inattention' rose by 15.4%, from 208 to 240 incidents. Conversely, crashes where 'No improper driving' was noted decreased by 16.9% in count, from 308 to 256. Crashes involving 'Disregarded traffic signs, signals, road markings' saw a notable 31.3% increase in count, rising from 32 to 42.
Officer-Reported Primary Contributing Cause
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
The majority of crashes in both periods occurred in 'Daylight' (71.9% in 2024 vs. 72.1% in 2023) and on 'Dry' road surfaces (82.3% vs. 82.4%). There was a slight shift in nighttime crash conditions, with the proportion of crashes on dark, unlighted roadways increasing from 6.1% to 7.3% of all incidents. Crashes on wet road surfaces decreased from 188 to 169 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes were stable, with Toyota, Ford, and Honda remaining the top three most common makes in both years. An analysis of persons involved shows a demographic shift, with the 65+ age group increasing from 478 to 504 individuals, a 5.4% rise. Conversely, the number of persons in the 16-20 age group involved in crashes decreased by 5.3%, from 285 to 270.
Top Vehicle Makes (2,334 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
176 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,678 persons with recorded sex)
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
There was a noticeable shift in crashes toward 30 mph speed zones, which saw a 16.6% increase from 368 to 429 incidents year-over-year, while crashes in 35 mph zones saw a slight 3.0% decrease. The distribution of fatal crashes across speed zones also changed; in 2024, one fatal crash occurred in a 55 mph zone where none were recorded in 2023. In contrast, 2023 saw a fatal crash in a 45 mph zone where none occurred in 2024.
Fatal crashes by zone: 30 mph: 1 of 429 (0.233%) · 35 mph: 2 of 288 (0.694%) · 55 mph: 1 of 87 (1.149%)
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: BARNSTABLE, MA
- Total crash records analyzed: 1,240
- Total persons involved: 2,910
- Total vehicles involved: 2,334
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). "BARNSTABLE, 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/barnstable/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved