ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GLOUCESTER, MA · MARCH 2023
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/gloucester/march-2023-report
Monthly Traffic Safety Analysis
34 CRASHES IN
GLOUCESTER, MA
MARCH 2023
In March 2023, Gloucester experienced 34 total crashes, marking a 15% decrease compared to the 40 crashes recorded in March 2022. Total injuries also saw a significant decline, from 11 to 8, a 27.3% reduction. The most notable shift was a 100% increase in single vehicle crashes, rising from 5 in the prior period to 10 in the current period.
34
▼ -15.0%was 40
Total Crash Events
0
Persons Killed
8
▼ -27.3%was 11
Persons Injured
1
▼ -50.0%was 2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Gloucester show a decline year-over-year. Total crashes decreased by 6, from 40 in March 2022 to 34 in March 2023, representing a 15% reduction. Similarly, total injuries fell by 3, from 11 to 8, a decrease of 27.3% compared to the prior year.
1
Hit-and-Run Crashes — March 2023
▼ -50.0% vs prior (2)
Hit-and-run crashes decreased from 2 in March 2022 to 1 in March 2023. The hit-and-run crash rate consequently decreased from 5% of total crashes in the prior period to 2.9% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Motorists Killed
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Thursday in both periods, with 10 crashes in March 2023, slightly down from 11 in March 2022. However, the peak hour shifted, with 12 p.m. recording the most crashes (7) in the prior period, while 3 p.m. saw the highest number of crashes (5) in the current period. Crashes on Tuesday decreased from 8 to 4, while Monday saw an increase from 1 to 2 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either March 2022 or March 2023. The proportion of crashes resulting in no injuries increased from 65% (26 crashes) in the prior period to 79.4% (27 crashes) in the current period. Minor injury crashes decreased from 5 (12.5% of total crashes) to 3 (8.8% of total crashes), and possible injury crashes also decreased from 4 (10% of total crashes) to 3 (8.8% of total crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'No improper driving' decreased significantly by 7 crashes, from 12 in March 2022 to 5 in March 2023, representing a 58.3% reduction. 'Inattention' increased by 2 crashes, from 4 to 6, a 50% rise. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 2 crashes, from 4 to 2, a 50% reduction, while 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' increased by 2 crashes, from 1 to 3, a 200% increase.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 31 in March 2022 to 20 in March 2023, while 'Cloudy' weather crashes increased from 1 to 6. Similarly, crashes on 'Dry' road surfaces decreased from 37 to 25. Crashes occurring in 'Daylight' conditions decreased from 32 to 25, while those in 'Dark - lighted roadway' conditions increased from 4 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 78 in March 2022 to 57 in March 2023. Toyota remained the most common make, though its involvement decreased from 14 to 13. Chevrolet, Honda, Nissan, and Subaru all saw decreases in their involvement. In terms of persons, the 21-25 age group saw the largest increase, from 4 to 10 persons involved, while the 26-34 age group experienced the largest decrease, from 15 to 7 persons involved.
Top Vehicle Makes (57 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (58 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 20 mph zones decreased from 7 in March 2022 to 2 in March 2023. Conversely, crashes in 30 mph zones increased from 1 to 4. Crashes in 55 mph zones decreased from 4 to 2, while crashes in 25 mph zones saw a slight increase from 10 to 11. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-03-01 through 2023-03-31 (31 days)
- Geographic scope: GLOUCESTER, MA
- Total crash records analyzed: 34
- Total persons involved: 67
- Total vehicles involved: 57
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 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/march-2023-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: 2023-03-01 – 2023-03-31
Generated: June 21, 2026 · All rights reserved