Monthly Traffic Safety Analysis

100 CRASHES IN
BARNSTABLE, MA
MAY 2022

All metrics benchmarked againstMay 2021

Total crashes in BARNSTABLE, MA increased by 47.06%, from 68 in May 2021 to 100 in May 2022. This period saw a significant year-over-year shift in hit-and-run incidents, which rose from 0 to 6 crashes.

100

47.1%was 68

Total Crash Events

0

Persons Killed

23

-8.0%was 25

Persons Injured

6

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in crashes, with total incidents rising from 68 in May 2021 to 100 in May 2022, marking a 47.06% increase. Despite this rise in crash volume, the number of total injuries slightly decreased from 25 to 23, representing an 8% reduction.

6

Hit-and-Run Crashes — May 2022

6.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 0%

1

Cyclists Injured

Prior: 0%

19

Motorists Injured

Prior: 25-24.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Monday in May 2021 (16 crashes) to Thursday in May 2022 (20 crashes). The peak hour remained consistent at 4 PM in both periods, though the number of crashes at this hour increased from 9 in May 2021 to 13 in May 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities reported in either May 2021 or May 2022. Total injuries decreased slightly from 25 in May 2021 to 23 in May 2022. The number of serious injuries remained constant at 1 in both periods, while minor injuries decreased from 11 to 10 and possible injuries increased from 4 to 6.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1%
0.0%prior 1
Minor Injury10minor injury crashes10%
-9.1%prior 11
Possible Injury6possible injury crashes6%
50.0%prior 4
No Injury81no injury crashes81%
55.8%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the top contributing factor, increasing from 20 crashes in May 2021 to 25 crashes in May 2022. 'No improper driving' saw the largest increase in count, rising from 8 crashes to 21 crashes, and its share of crashes increased from 11.8% to 21%. 'Failed to yield right of way' decreased slightly from 11 crashes to 10 crashes, while 'Followed too closely' increased from 5 crashes to 8 crashes.

Officer-Reported Primary Contributing Cause

Inattention25 (25%)25.0%prior 20
No improper driving21 (21%)162.5%prior 8
Failed to yield right of way10 (10%)-9.1%prior 11
Followed too closely8 (8%)60.0%prior 5
Distracted6 (6%)
Failure to keep in proper lane or running off road5 (5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (4%)
Physical impairment3 (3%)
Other improper action2 (2%)
Disregarded traffic signs, signals, road markings2 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 52 in May 2021 to 71 in May 2022. The number of crashes during 'Daylight' conditions also rose from 55 to 78. Incidents on 'Dry' road surfaces increased significantly from 56 to 87, while crashes on 'Wet' surfaces saw a smaller increase from 11 to 13.

Weather

Clear71 (71.0%)
36.5%prior 52
Cloudy8 (8.0%)
Rain6 (6.0%)
-14.3%prior 7
Cloudy/Rain3 (3.0%)
Clear/Cloudy3 (3.0%)
Fog, smog, smoke2 (2.0%)
Clear/Other2 (2.0%)
Rain/Fog, smog, smoke1 (1.0%)
Clear/Unknown1 (1.0%)
Cloudy/Clear1 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash

Lighting

Daylight78 (78.0%)
41.8%prior 55
Dark - lighted roadway15 (15.0%)
66.7%prior 9
Dark - roadway not lighted5 (5.0%)
Dusk2 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field

Road Surface

Dry87 (87.0%)
55.4%prior 56
Wet13 (13.0%)
18.2%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 127 in May 2021 to 182 in May 2022. FORD vehicles moved from the second most involved make to the first, with its count rising from 19 to 33, while TOYOTA, previously first, increased from 23 to 29. The age group with the largest increase in persons involved was 45-54, rising from 12 to 29, and the 35-44 and 65+ age groups each increased by 10 persons.

Top Vehicle Makes (182 vehicles)

1
FORD33 (18.1%)
73.7%prior 19
2
TOYOTA29 (15.9%)
26.1%prior 23
3
HONDA15 (8.2%)
-11.8%prior 17
4
CHEVROLET13 (7.1%)
18.2%prior 11
5
NISSAN10 (5.5%)
6
GMC10 (5.5%)
7
JEEP9 (4.9%)
0.0%prior 9
8
HYUNDAI7 (3.8%)
9
SUBARU6 (3.3%)
10
AUDI5 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records

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

Sex Distribution (215 persons with recorded sex)

Male131 (60.9%)
47.2%prior 89
Female84 (39.1%)
10.5%prior 76

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone saw the largest increase, rising from 16 in May 2021 to 31 in May 2022. Crashes in the 35 mph zone also increased from 15 to 22, and the 55 mph zone saw an increase from 3 to 8 crashes. There were no fatal crashes recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-05-01 through 2022-05-31 (31 days)
  • Geographic scope: BARNSTABLE, MA
  • Total crash records analyzed: 100
  • Total persons involved: 232
  • Total vehicles involved: 182

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: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/barnstable/may-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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Barnstable, MA Crash Report — May 2022 | ThatCarHitMe.com