ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GLOUCESTER, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
564 CRASHES IN
GLOUCESTER, MA
2024
In 2024, Gloucester recorded 564 total vehicle crashes, representing a 7.4% decrease from the 609 crashes reported in 2023. While total injuries saw a slight increase, the most significant year-over-year change was the reduction in traffic fatalities. The city experienced zero fatal crashes in 2024, down from one fatal crash in the prior year.
564
▼ -7.4%was 609
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
122
▲ 8.9%was 112
Persons Injured
57
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. 43 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic crashes in Gloucester decreased by 7.4% from 609 in 2023 to 564 in 2024. Despite the drop in total collisions, the number of people injured in these incidents rose by 8.9%, from 112 to 122. Fatalities were eliminated, falling from one in the prior year to zero in the current period.
57
Hit-and-Run Crashes — 2024
▼ 0.0% vs prior (57)
The absolute number of hit-and-run crashes remained unchanged year-over-year, with 57 incidents recorded in both 2023 and 2024. However, due to the overall decrease in total crashes in 2024, the hit-and-run rate increased. Hit-and-runs constituted 10.1% of all crashes in 2024, up from a rate of 9.4% in the prior year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
8
Pedestrians Injured
8
Cyclists Injured
103
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The daily pattern of crashes shifted year-over-year, with Friday remaining a peak day for collisions in both 2023 (102 crashes) and 2024 (99 crashes). However, Tuesday, which was a joint peak day in 2023, saw a notable drop in incidents, while Monday became the second-highest day in 2024 with 97 crashes. The peak hour for crashes moved two hours earlier, shifting from 3 PM in 2023 (55 crashes) to 1 PM in 2024 (54 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The most significant change in crash severity was the elimination of fatalities, with fatal crashes dropping from one in 2023 to zero in 2024. The number of serious injury crashes remained unchanged at five incidents. However, crashes resulting in minor or possible injuries both increased; minor injury crashes rose from 50 to 55, and possible injury crashes increased from 32 to 43. Consequently, the proportion of all crashes resulting in some form of reported injury grew from 14.3% in 2023 to 18.3% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors to crashes remained consistent between both years, though their counts varied. Crashes attributed to "Inattention" decreased by count from 55 in 2023 to 39 in 2024, a 29% reduction. Similarly, crashes involving a "Distracted" driver fell from 24 to 19. Conversely, the count of crashes where "No improper driving" was cited increased from 184 to 225. Slight increases were also observed in crashes due to "Failed to yield right of way" (from 26 to 28) and "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" (from 25 to 27).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions under which crashes occurred showed some shifts between the two periods. The number of crashes on wet road surfaces decreased from 86 in 2023 to 59 in 2024, and their share of total crashes fell from 14.1% to 10.5%. Correspondingly, the proportion of crashes on dry roads increased from 83.1% to 86.0%. While the number of crashes during daylight hours fell from 454 to 395, their share of the total also decreased from 74.5% to 70.0%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda being the top three in both years. In 2024, Honda (111 vehicles) surpassed Ford (99 vehicles) to become the second most common make, a reversal from 2023 when Ford (130) ranked ahead of Honda (97). Analysis of persons involved in crashes shows a notable shift in the 65+ age group, which grew from 201 individuals (16.3% of persons) in 2023 to 219 individuals (19.3% of persons) in 2024.
Top Vehicle Makes (1,032 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
214 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (904 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The 25 mph speed zone consistently accounted for the highest number of crashes in both periods, with 250 incidents in 2023 and 233 in 2024. A significant year-over-year change was observed in zones with a 55 mph speed limit, where the number of crashes increased from 27 to 49. The one fatal crash recorded in 2023 occurred within a 20 mph zone; there were no fatal crashes in any speed zone in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: GLOUCESTER, MA
- Total crash records analyzed: 564
- Total persons involved: 1,133
- Total vehicles involved: 1,032
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved