ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · JUNE 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/chelsea/june-2022-report
Monthly Traffic Safety Analysis
60 CRASHES IN
CHELSEA, MA
JUNE 2022
For June 2022, Chelsea experienced 60 total crashes, which is consistent with the 60 crashes recorded in June 2021. Despite stable crash numbers, total injuries decreased by 25%, falling from 28 in June 2021 to 21 in June 2022. This reduction in injuries represents the most significant year-over-year shift for the period.
60
Total Crash Events
0
Persons Killed
21
▼ -25.0%was 28
Persons Injured
3
▲ 50.0%was 2
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 · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in Chelsea remained stable year-over-year, with 60 crashes reported in June 2022, identical to the 60 crashes in June 2021. However, total injuries saw a notable decrease of 25%, falling from 28 injured persons in June 2021 to 21 injured persons in June 2022.
3
Hit-and-Run Crashes — June 2022
▲ 50.0% vs prior (2)
Hit-and-run crashes increased from 2 incidents in June 2021 to 3 incidents in June 2022. This represents an increase in the hit-and-run crash rate from 3.3% to 5% of all crashes year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
3
Cyclists Injured
16
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes showed some shifts year-over-year. In June 2022, the peak day for crashes was Thursday with 11 incidents, compared to Saturday with 10 incidents in June 2021. The peak crash hour also shifted from 7 AM in June 2021 to 2 PM in June 2022, both periods recording 6 crashes at their respective peak hours.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either June 2022 or June 2021. The number of serious injuries (severity 'A') increased from 2 in June 2021 to 3 in June 2022. Conversely, minor injuries (severity 'B') decreased from 9 to 5, and possible injuries (severity 'C') also decreased from 9 to 5, contributing to the overall 25% reduction in total injuries.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'No improper driving' remained the most frequently cited, increasing by 9 crashes from 16 in June 2021 to 25 in June 2022. 'Inattention' also saw a slight increase, from 3 crashes in the prior period to 4 crashes in the current period. Notably, factors like 'Exceeded authorized speed limit' decreased from 2 crashes to 0, and 'Distracted' decreased from 2 crashes to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased slightly from 55 in June 2021 to 52 in June 2022. Concurrently, crashes during rainy conditions increased from 1 to 3, and crashes on wet road surfaces increased from 4 to 5. The proportion of crashes occurring in daylight increased from 44 to 47, while those occurring at dusk decreased from 4 to 1.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes showed some shifts year-over-year. Toyota remained the most common make, increasing from 29 vehicles in June 2021 to 31 in June 2022. Ford saw a significant increase in involvement, rising from 11 vehicles to 20, while Nissan's involvement decreased notably from 13 vehicles to 4.
Top Vehicle Makes (109 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (120 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both periods occurred in the 25 MPH speed zone, though the count decreased from 44 in June 2021 to 39 in June 2022. Conversely, crashes in the 20 MPH zone increased from 1 to 6, and in the 40 MPH zone, they increased from 1 to 4. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-06-01 through 2022-06-30 (30 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 60
- Total persons involved: 131
- Total vehicles involved: 109
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). "CHELSEA, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/june-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: 2022-06-01 – 2022-06-30
Generated: June 21, 2026 · All rights reserved