ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SHREWSBURY, 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/shrewsbury/may-2022-report
Monthly Traffic Safety Analysis
60 CRASHES IN
SHREWSBURY, MA
MAY 2022
In May 2022, Shrewsbury experienced 60 total crashes, a decrease of 13.04% compared to the 69 crashes reported in May 2021. While total crashes declined, DUI-related crashes saw a significant increase, rising from 1 in May 2021 to 3 in May 2022, representing a 200% surge. Fatalities remained at zero for both periods.
60
▼ -13.0%was 69
Total Crash Events
0
Persons Killed
13
▼ -7.1%was 14
Persons Injured
6
▲ 50.0%was 4
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. 4 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
The overall trend for May 2022 indicates a decrease in crash incidents in Shrewsbury, with total crashes falling by 13.04% from 69 in the prior year to 60. Total injuries also saw a slight decline, decreasing from 14 to 13. There were no fatal crashes reported in either May 2021 or May 2022.
6
Hit-and-Run Crashes — May 2022
▲ 50.0% vs prior (4)
Hit-and-run crashes increased year-over-year, rising from 4 incidents in May 2021 to 6 incidents in May 2022. This represents a 50% increase in the count of hit-and-run crashes. The hit-and-run rate also increased from 5.8% of total crashes in May 2021 to 10% in May 2022.
Vulnerable Road User Casualties
0
Motorists Killed
13
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. In May 2022, Thursday became the peak day for crashes with 14 incidents, while May 2021 saw Friday and Thursday equally as peak days with 13 crashes each. The peak hour also changed, moving from 5 PM with 9 crashes in May 2021 to 4 PM with 7 crashes in May 2022.
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
The severity distribution of crashes changed notably, with serious injuries (code A) appearing in May 2022 with 2 incidents, compared to zero in May 2021. Minor injuries (code B) decreased from 7 in May 2021 to 4 in May 2022, a 42.86% reduction. Possible injuries (code C) also decreased from 3 to 2, representing a 33.33% decline.
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 showed notable changes year-over-year. Crashes attributed to "No improper driving" increased from 12 in May 2021 to 15 in May 2022, a 25% increase in count. Conversely, "Inattention" as a factor decreased from 10 crashes to 7 crashes, a 30% reduction. "Followed too closely" also saw a significant decrease, dropping from 9 crashes to 2 crashes, a 77.78% reduction in count.
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
Weather conditions for crashes remained predominantly clear in both periods, with 40 crashes occurring in clear weather in May 2022 compared to 48 in May 2021. Daylight remained the dominant lighting condition for crashes, accounting for 51 incidents in May 2022 and 53 in May 2021. Road surface conditions were primarily dry, with 56 dry-road crashes in May 2022, a slight decrease from 60 in May 2021, while wet-road crashes decreased from 6 to 3.
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 persons involved in crashes decreased from 151 in May 2021 to 144 in May 2022. The 16-20 age group saw a decrease in involved persons from 25 to 19, while the 35-44 age group increased from 19 to 23. Toyota remained the top vehicle make involved in crashes, with 21 vehicles in May 2022 compared to 22 in May 2021.
Top Vehicle Makes (120 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (134 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 40 MPH speed zones saw a significant decrease, falling from 12 in May 2021 to 6 in May 2022. Conversely, crashes in 30 MPH speed zones increased from 6 to 9. The number of crashes in 65 MPH speed zones remained stable at 5 for both periods. No fatal crashes were recorded in any speed zone during either period.
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: SHREWSBURY, MA
- Total crash records analyzed: 60
- Total persons involved: 144
- Total vehicles involved: 120
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). "SHREWSBURY, 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/shrewsbury/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