Monthly Traffic Safety Analysis

37 CRASHES IN
GLOUCESTER, MA
APRIL 2022

All metrics benchmarked againstApril 2021

Total crashes in Gloucester decreased by 27.45% year-over-year, from 51 crashes in April 2021 to 37 crashes in April 2022. Concurrently, total injuries decreased by 33.33%, from 12 to 8. A notable shift was observed in hit-and-run incidents, which increased from 1 crash to 6 crashes.

37

-27.5%was 51

Total Crash Events

0

Persons Killed

8

-33.3%was 12

Persons Injured

6

500.0%was 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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Gloucester shows a downward trend year-over-year. Total crashes decreased by 14 incidents, representing a 27.45% reduction from 51 in April 2021 to 37 in April 2022. Similarly, total injuries also decreased from 12 to 8, a 33.33% decline.

6

Hit-and-Run Crashes — April 2022

500.0% vs prior (1)

Hit-and-run crashes saw a significant increase year-over-year, rising from 1 incident in April 2021 to 6 incidents in April 2022. This change represents an increase in the hit-and-run rate from 2% to 16.2% of all crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 11-27.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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 Friday in April 2021, which saw 14 crashes, to Friday and Saturday in April 2022, both recording 9 crashes. The peak hour for crashes also changed, moving from 8 AM with 7 crashes in the prior period to 11 AM with 5 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either period. The number of persons injured decreased from 12 in April 2021 to 8 in April 2022. The current period saw 1 crash with serious injury (2.7% share of crashes), which was not present in the prior period's data, while minor injury crashes decreased from 7 (13.7% share) to 4 (10.8% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.7%
Minor Injury4minor injury crashes10.8%
-42.9%prior 7
Possible Injury1possible injury crashes2.7%
-75.0%prior 4
No Injury25no injury crashes67.6%
-32.4%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'No improper driving' decreased from 17 (33.3% share) in April 2021 to 7 (18.9% share) in April 2022. Conversely, 'Inattention' as a contributing factor increased from 3 crashes (5.9% share) to 6 crashes (16.2% share). 'Distracted' driving also saw an increase, from 1 crash (2% share) to 3 crashes (8.1% share) year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving7 (18.9%)-58.8%prior 17
Inattention6 (16.2%)
Distracted3 (8.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5.4%)
Other improper action2 (5.4%)
Exceeded authorized speed limit2 (5.4%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.7%)
Fatigued/asleep1 (2.7%)
Driving too fast for conditions1 (2.7%)
Followed too closely1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under 'Clear' weather conditions increased from 25 in April 2021 to 32 in April 2022. Crashes during 'Daylight' decreased from 40 to 29, and those in 'Dark - lighted roadway' conditions decreased from 9 to 4. Crashes on 'Dry' road surfaces decreased from 39 to 32, and on 'Wet' surfaces from 11 to 4.

Weather

Clear32 (88.9%)
28.0%prior 25
Rain3 (8.3%)
Cloudy/Rain1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Weather condition at time of crash

Lighting

Daylight29 (80.6%)
-27.5%prior 40
Dark - lighted roadway4 (11.1%)
-55.6%prior 9
Dark - roadway not lighted1 (2.8%)
Dark - unknown roadway lighting1 (2.8%)
Dawn1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Lighting condition field

Road Surface

Dry32 (88.9%)
-17.9%prior 39
Wet4 (11.1%)
-63.6%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 91 in April 2021 to 71 in April 2022. TOYOTA became the top vehicle make involved in crashes with 10 incidents, surpassing FORD which decreased from 15 to 8. All age groups generally saw a decrease in persons involved, with the 21-25 age group experiencing a notable reduction from 15 to 5 persons.

Top Vehicle Makes (71 vehicles)

1
TOYOTA10 (14.1%)
11.1%prior 9
2
FORD8 (11.3%)
-46.7%prior 15
3
CHEVROLET8 (11.3%)
60.0%prior 5
4
HONDA7 (9.9%)
16.7%prior 6
5
SUBARU7 (9.9%)
40.0%prior 5
6
GMC4 (5.6%)
7
JEEP3 (4.2%)
-62.5%prior 8
8
DODGE3 (4.2%)
9
AUDI2 (2.8%)
10
KIA2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Vehicle unit records

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

Sex Distribution (58 persons with recorded sex)

Male40 (69.0%)
-23.1%prior 52
Female18 (31.0%)
-51.4%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · Person-level records linked to crash events

Speed Limit Zones

The total number of crashes with a recorded speed limit decreased from 34 in April 2021 to 20 in April 2022. Crashes in 20 mph zones decreased from 7 to 2, and in 25 mph zones from 13 to 10. There were no fatal crashes reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-04-01 to 2022-04-30 · 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: 2022-04-01 through 2022-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-04-01 through 2022-04-30 (30 days)
  • Geographic scope: GLOUCESTER, MA
  • Total crash records analyzed: 37
  • Total persons involved: 76
  • Total vehicles involved: 71

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). "GLOUCESTER, MA Crash Intelligence Report: April 2022." Published June 21, 2026. Reporting period: 2022-04-01 to 2022-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/april-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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Gloucester, MA Crash Report — April 2022 | ThatCarHitMe.com