ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · MAY 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/marlborough/may-2024-report
Monthly Traffic Safety Analysis
115 CRASHES IN
MARLBOROUGH, MA
MAY 2024
In May 2024, MARLBOROUGH experienced 115 total crashes, an increase of 16 crashes from the 99 recorded in May 2023, representing a 16.16% rise. The most notable year-over-year shift was in hit-and-run incidents, which surged from 3 crashes in May 2023 to 14 crashes in May 2024, marking a 366.67% increase.
115
▲ 16.2%was 99
Total Crash Events
0
Persons Killed
12
▼ -55.6%was 27
Persons Injured
14
▲ 366.7%was 3
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend indicates a rise in total crashes, increasing by 16.16% from 99 crashes in May 2023 to 115 crashes in May 2024. Despite the increase in total crashes, total injuries decreased by 55.56%, from 27 in May 2023 to 12 in May 2024.
14
Hit-and-Run Crashes — May 2024
▲ 366.7% vs prior (3)
Hit-and-run crashes increased significantly from 3 in May 2023 to 14 in May 2024, representing a 366.67% increase. The hit-and-run rate also saw a substantial increase, rising from 3% of total crashes in May 2023 to 12.2% in May 2024, indicating an upward trend.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
2
Cyclists Injured
10
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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 Tuesday with 22 crashes in May 2023 to Wednesday with 28 crashes in May 2024. The peak hour for crashes remained 3p for both periods, although the count slightly decreased from 13 crashes in May 2023 to 12 crashes in May 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either May 2023 or May 2024. The proportion of crashes resulting in no injury increased from 78.8% (78 crashes) in May 2023 to 87.8% (101 crashes) in May 2024. Minor injuries decreased from 14 crashes (14.1% share) in May 2023 to 7 crashes (6.1% share) in May 2024, and possible injuries decreased from 5 crashes (5.1% share) to 4 crashes (3.5% share) during the same period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving,' increased by 20 crashes, from 16 in May 2023 to 36 in May 2024, moving it from third to first in ranking. Conversely, 'Inattention' decreased by 4 crashes, from 24 to 20, and 'Followed too closely' decreased by 6 crashes, from 17 to 11, between the two periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in wet road conditions significantly increased from 7 in May 2023 to 23 in May 2024. Similarly, crashes in dark conditions (lighted, unlighted, unknown) rose from 11 to 23. The proportion of crashes occurring in clear weather decreased from 82.8% to 73%, and on dry road surfaces from 91.9% to 80%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 203 in May 2023 to 219 in May 2024. Among top makes, TOYOTA saw a decrease from 44 to 39, while HONDA increased from 23 to 29 and FORD from 23 to 28. In terms of persons involved, the 0-15 age group increased from 8 to 32, and the 35-44 age group increased from 26 to 51, while the 16-20 age group decreased from 40 to 34 and the 26-34 age group decreased from 55 to 39.
Top Vehicle Makes (219 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records
32 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (245 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone increased from 26 in May 2023 to 35 in May 2024, and in the 35 mph zone, they significantly rose from 11 to 28. Conversely, crashes in the 25 mph zone decreased from 20 to 15, in the 40 mph zone from 16 to 9, and in the 65 mph zone from 14 to 11. There were no fatal crashes in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-05-01 through 2024-05-31 (31 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 115
- Total persons involved: 284
- Total vehicles involved: 219
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). "MARLBOROUGH, MA Crash Intelligence Report: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/may-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-05-01 – 2024-05-31
Generated: June 21, 2026 · All rights reserved