Monthly Traffic Safety Analysis

14 CRASHES IN
SCITUATE, MA
JUNE 2022

All metrics benchmarked againstJune 2021

In June 2022, SCITUATE experienced 14 crashes, a 50% decrease compared to the 28 crashes recorded in June 2021. Total injuries also decreased by 57.1%, from 7 in June 2021 to 3 in June 2022. The most notable year-over-year shift is the significant reduction in overall crash and injury counts.

14

▼ -50.0%was 28

Total Crash Events

0

Persons Killed

3

▼ -57.1%was 7

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 · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in SCITUATE showed a declining trend year-over-year, with total crashes decreasing by 50% from 28 in June 2021 to 14 in June 2022. This reduction indicates a substantial decrease in crash incidents during the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 0→0.0%

2

Cyclists Injured

Prior: 1↑100.0%

1

Motorists Injured

Prior: 6↓-83.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 Thursday with 6 crashes in June 2021 to Tuesday with 5 crashes in June 2022. Similarly, the peak hour changed from 12p with 6 crashes in June 2021 to 4p with 2 crashes in June 2022. Crashes in June 2022 were more evenly distributed throughout the day with lower counts per hour compared to June 2021.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either June 2021 or June 2022. Total injuries decreased from 7 in June 2021 to 3 in June 2022, a 57.1% reduction. The proportion of crashes with 'No Injury' increased from 71.4% in June 2021 to 78.6% in June 2022, while 'Serious Injury' crashes (3.6%) observed in June 2021 were not present in June 2022.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes7.1%
↓-66.7%prior 3
Possible Injury2possible injury crashes14.3%
→0.0%prior 2
No Injury11no injury crashes78.6%
↓-45.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased by 3, from 9 in June 2021 to 6 in June 2022. 'Failed to yield right of way' crashes decreased by 1, from 2 to 1, while 'Inattention' crashes increased by 1, from 1 to 2. Factors such as 'Followed too closely' (2 crashes) and 'Disregarded traffic signs, signals, road markings' (2 crashes) were among the top factors in June 2021 but not in June 2022, whereas 'Other improper action' (2 crashes) was a top factor in June 2022 but not in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving6 (42.9%)↓-33.3%prior 9
Other improper action2 (14.3%)
Inattention2 (14.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (7.1%)
Failed to yield right of way1 (7.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

All 14 crashes in June 2022 occurred under clear or clear/unknown weather conditions, a change from June 2021 where 11 out of 28 crashes occurred in non-clear conditions such as rain or cloudy weather. Crashes during daylight decreased from 21 in June 2021 to 12 in June 2022. Road surface conditions cannot be compared as data for June 2022 is unavailable.

Weather

Clear13 (92.9%)
↓-23.5%prior 17
Clear/Unknown1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight12 (85.7%)
↓-42.9%prior 21
Dark - lighted roadway1 (7.1%)
↓-80.0%prior 5
Dark - roadway not lighted1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (22 vehicles)

1
TOYOTA5 (22.7%)
↓-16.7%prior 6
2
JEEP3 (13.6%)
3
FORD2 (9.1%)
↓-81.8%prior 11
4
HONDA2 (9.1%)
5
AUDI2 (9.1%)
6
CHEVROLET2 (9.1%)
7
HYUNDAI1 (4.5%)
8
MERCEDES-BENZ1 (4.5%)
9
NISSAN1 (4.5%)
10
SUBARU1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

Sex Distribution (21 persons with recorded sex)

Male12 (57.1%)
↓-55.6%prior 27
Female9 (42.9%)
↓-59.1%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded across any speed zone in either period. Crashes in the 30 mph zone significantly decreased from 13 in June 2021 to 2 in June 2022. Crashes in the 25 mph and 35 mph zones also decreased, from 4 to 3 and 5 to 3 respectively. The number of crashes in the 50 mph zone remained constant at 4 in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: SCITUATE, MA
  • Total crash records analyzed: 14
  • Total persons involved: 24
  • Total vehicles involved: 22

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). "SCITUATE, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/scituate/june-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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Scituate, MA Crash Report — June 2022 | ThatCarHitMe.com