ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · MAY 2022
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-2022-report
Monthly Traffic Safety Analysis
71 CRASHES IN
MARLBOROUGH, MA
MAY 2022
In May 2022, Marlborough experienced 71 crashes, a decrease of 15.47% from the 84 crashes recorded in May 2021. A notable positive shift was the absence of fatalities in May 2022, compared to one fatality in May 2021. Total injuries also saw a slight decrease from 20 to 19.
71
▼ -15.5%was 84
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
19
▼ -5.0%was 20
Persons Injured
2
▲ 100.0%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 · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Marlborough decreased year-over-year, with total crashes falling by 15.47% from 84 in May 2021 to 71 in May 2022. Fatalities dropped from one to zero, while total injuries slightly decreased from 20 to 19. This indicates a general downward trend in crash frequency and severity.
2
Hit-and-Run Crashes — May 2022
▲ 100.0% vs prior (1)
Hit-and-run crashes increased by 100% year-over-year, rising from 1 crash in May 2021 to 2 crashes in May 2022. Consequently, the hit-and-run rate also increased from 1.2% to 2.8%. This indicates an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
2
Cyclists Injured
17
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year, with the peak day changing from Saturday (13 crashes) in May 2021 to Tuesday (15 crashes) in May 2022. The peak hour also moved from 6 PM (8 crashes) in May 2021 to 2 PM (11 crashes) in May 2022. This suggests a change in when the highest concentration of crashes occurred.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Marlborough saw a positive shift in crash severity, with no fatal crashes or fatalities recorded in May 2022, compared to one fatal crash and one fatality in May 2021. Serious injuries (Severity A) decreased by 66.67% from 3 to 1, and minor injuries (Severity B) decreased by 25% from 8 to 6. Conversely, possible injuries (Severity C) increased by 33.33% from 6 to 8.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable count changes year-over-year. Crashes attributed to 'Failure to keep in proper lane or running off road' increased by 400%, from 1 to 5, while 'Disregarded traffic signs, signals, road markings' crashes increased by 200%, from 1 to 3. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' crashes decreased by 80%, from 5 to 1, and 'No improper driving' crashes decreased by 25%, from 20 to 15.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather conditions remained dominant, though the count decreased from 66 to 61 year-over-year. Crashes during daylight hours decreased from 69 to 54, while those occurring in 'Dark - roadway not lighted' conditions increased from 3 to 7. The number of crashes on dry road surfaces decreased from 76 to 65, consistent with the overall reduction in total crashes.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 157 in May 2021 to 127 in May 2022. The age group '0-15' saw a substantial increase in persons involved in crashes, rising from 5 to 32. Toyota and Ford remained the top two most frequently involved vehicle makes, though their counts decreased from 31 to 19 and 26 to 17 respectively.
Top Vehicle Makes (127 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (154 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone decreased by 8 crashes, from 18 to 10, while crashes in the 30 mph zone remained relatively stable, increasing slightly from 25 to 26. The 30 mph speed zone was the only one to record a fatal crash in May 2021 (1 fatal crash, 4% fatal rate), with no fatal crashes reported in any speed zone in May 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-05-01 through 2022-05-31 (31 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 71
- Total persons involved: 176
- Total vehicles involved: 127
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 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/may-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-05-01 – 2022-05-31
Generated: June 21, 2026 · All rights reserved