Monthly Traffic Safety Analysis

44 CRASHES IN
GLOUCESTER, MA
MARCH 2024

All metrics benchmarked againstMarch 2023

Total crashes in Gloucester increased by 29.4% year-over-year, rising from 34 in March 2023 to 44 in March 2024. This period also saw a significant increase in hit-and-run incidents, which surged by 300% from 1 crash to 4 crashes. Overall injuries also increased by 62.5%, from 8 to 13.

44

29.4%was 34

Total Crash Events

0

Persons Killed

13

62.5%was 8

Persons Injured

4

300.0%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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in crash activity in Gloucester, with total crashes rising from 34 in March 2023 to 44 in March 2024. This represents a 29.4% increase in total crashes. Concurrently, total injuries increased by 62.5%, from 8 to 13.

4

Hit-and-Run Crashes — March 2024

300.0% vs prior (1)

Hit-and-run crashes increased significantly, from 1 incident in March 2023 to 4 incidents in March 2024, representing a 300% increase in count. The hit-and-run rate also rose from 2.9% of all crashes to 9.1% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

13

Motorists Injured

Prior: 862.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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 Thursday in March 2023 (10 crashes) to Monday in March 2024 (11 crashes). Thursday crashes decreased from 10 to 4, while Monday crashes significantly increased from 2 to 11. The peak hour also shifted, with 1 PM becoming the new peak in March 2024 with 7 crashes, compared to 3 PM with 5 crashes in March 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either March 2023 or March 2024. The number of minor injury crashes increased from 3 to 6, and possible injury crashes increased from 3 to 4. Overall, crashes resulting in any injury accounted for 17.6% of crashes in March 2023 (6 of 34) and 22.7% in March 2024 (10 of 44).

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes13.6%
100.0%prior 3
Possible Injury4possible injury crashes9.1%
33.3%prior 3
No Injury32no injury crashes72.7%
18.5%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'No improper driving' was cited increased from 5 in March 2023 to 12 in March 2024. Conversely, crashes attributed to 'Inattention' decreased from 6 to 2. 'Failed to yield right of way' saw a notable increase in count from 1 to 6, while 'Distracted' crashes decreased from 3 to 1.

Officer-Reported Primary Contributing Cause

No improper driving12 (27.3%)140.0%prior 5
Failed to yield right of way6 (13.6%)
Inattention2 (4.5%)-66.7%prior 6
Glare2 (4.5%)
Illness2 (4.5%)
Made an improper turn2 (4.5%)
Other improper action2 (4.5%)
Visibility obstructed2 (4.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.3%)
Distracted1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions increased from 25 in March 2023 to 31 in March 2024, and those in 'Dark - lighted roadway' conditions increased from 6 to 11. The number of crashes on 'Dry' road surfaces increased from 25 to 37. Crashes during 'Snow' conditions, which accounted for 1 incident in March 2023, were not reported in March 2024.

Weather

Clear23 (52.3%)
15.0%prior 20
Clear/Other7 (15.9%)
Cloudy6 (13.6%)
0.0%prior 6
Rain3 (6.8%)
Clear/Cloudy2 (4.5%)
Rain/Fog, smog, smoke1 (2.3%)
Cloudy/Rain1 (2.3%)
Rain/Cloudy1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Weather condition at time of crash

Lighting

Daylight31 (70.5%)
24.0%prior 25
Dark - lighted roadway11 (25.0%)
83.3%prior 6
Dark - roadway not lighted1 (2.3%)
Dusk1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Lighting condition field

Road Surface

Dry37 (84.1%)
48.0%prior 25
Wet7 (15.9%)
40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 57 in March 2023 to 84 in March 2024. Toyota remained the top make involved, increasing from 13 to 17 vehicles. Honda saw a substantial increase in involvement, from 2 vehicles to 10 vehicles, while Ford involvement decreased from 7 to 4 vehicles. The 26-34 age group saw a rise in persons involved from 7 to 14, and the 65+ age group increased from 10 to 17 persons, whereas the 21-25 age group decreased from 10 to 4 persons involved.

Top Vehicle Makes (84 vehicles)

1
TOYOTA17 (20.2%)
30.8%prior 13
2
HONDA10 (11.9%)
3
JEEP9 (10.7%)
4
CHEVROLET6 (7.1%)
5
NISSAN5 (6%)
6
GMC4 (4.8%)
7
FORD4 (4.8%)
-42.9%prior 7
8
HYUNDAI3 (3.6%)
9
SUBARU3 (3.6%)
10
ACURA2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Vehicle unit records

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

Sex Distribution (73 persons with recorded sex)

Male39 (53.4%)
25.8%prior 31
Female34 (46.6%)
25.9%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 11 in March 2023 to 20 in March 2024. Crashes in 30 mph zones decreased from 4 to 2, and in 55 mph zones, they slightly increased from 2 to 3. Notably, 5 mph and 45 mph speed zones each recorded 1 crash in March 2024, neither of which appeared in the March 2023 data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-03-01 to 2024-03-31 · 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: 2024-03-01 through 2024-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-03-01 through 2024-03-31 (31 days)
  • Geographic scope: GLOUCESTER, MA
  • Total crash records analyzed: 44
  • Total persons involved: 88
  • Total vehicles involved: 84

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: March 2024." Published June 21, 2026. Reporting period: 2024-03-01 to 2024-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/march-2024-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 — March 2024 | ThatCarHitMe.com