ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WELLESLEY, 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/wellesley/may-2022-report
Monthly Traffic Safety Analysis
40 CRASHES IN
WELLESLEY, MA
MAY 2022
Total crashes in Wellesley decreased slightly from 41 in May 2021 to 40 in May 2022, representing a 2.4% reduction. Despite this small decrease in overall incidents, total injuries rose by 41.7%, from 12 to 17. This suggests a notable shift towards more severe outcomes in crashes.
40
▼ -2.4%was 41
Total Crash Events
0
Persons Killed
17
▲ 41.7%was 12
Persons Injured
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. 1 crash with unreported severity is 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 incidents in Wellesley saw a minor decrease of 2.4% year-over-year, with 40 crashes recorded in May 2022 compared to 41 in May 2021. However, total injuries increased by 41.7%, rising from 12 to 17 during the same period. This indicates a trend of fewer but potentially more impactful crashes.
1
Hit-and-Run Crashes — May 2022
▼ 0.0% vs prior (1)
The number of hit-and-run crashes remained stable at 1 incident in both May 2021 and May 2022. The hit-and-run crash rate saw a slight increase from 2.4% in May 2021 to 2.5% in May 2022. This indicates a consistent occurrence of hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
3
Pedestrians Injured
14
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 peak day for crashes shifted from Monday (9 crashes) in May 2021 to Friday (7 crashes) in May 2022. The peak crash hour remained 5 PM for both periods, though the count decreased from 6 crashes in May 2021 to 5 crashes in May 2022. Crash distribution across days of the week appears more even in May 2022 compared to the prior year.
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
While there were no fatalities in either May 2021 or May 2022, total injuries increased by 41.7%, from 12 to 17. Serious injuries (code A) rose from 0 in May 2021 to 2 in May 2022, and possible injuries (code C) increased from 3 to 4. Minor injuries (code B) decreased from 8 to 5, but the overall injury count rose.
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
Inattention as a contributing factor doubled in count, increasing from 4 crashes in May 2021 to 8 crashes in May 2022. Crashes attributed to 'Made an improper turn' also saw a significant rise, from 1 to 3 incidents. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 3 crashes to 1, and 'Followed too closely' also dropped from 3 to 1 crash. 'No improper driving' remained consistent at 12 crashes for both periods.
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 number of crashes occurring in 'Daylight' conditions decreased from 36 in May 2021 to 31 in May 2022. Concurrently, crashes in 'Dark - lighted roadway' conditions increased from 4 to 6 incidents. The prevalence of 'Clear' weather conditions in crashes rose slightly from 28 to 30, while crashes in 'Rain' decreased from 3 to 1.
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 by 11.25%, from 80 in May 2021 to 71 in May 2022. Toyota remained the top vehicle make involved, though its count dropped from 14 to 9. The age group 45-54 saw a notable decrease in persons involved, from 17 to 8, while the 16-20 age group saw an increase from 11 to 13.
Top Vehicle Makes (71 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (80 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 occurring in 50 mph speed zones saw a substantial decrease, dropping from 14 in May 2021 to 4 in May 2022. Conversely, crashes in 55 mph speed zones increased from 0 to 7 incidents. Crashes in 30 mph zones rose from 21 to 24, while 10 mph and 40 mph zones each saw a decrease of 2 crashes, from 2 to 0.
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: WELLESLEY, MA
- Total crash records analyzed: 40
- Total persons involved: 85
- Total vehicles involved: 71
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). "WELLESLEY, 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/wellesley/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