ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · JANUARY 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/january-2022-report
Monthly Traffic Safety Analysis
85 CRASHES IN
CHELSEA, MA
JANUARY 2022
In January 2022, CHELSEA, MA experienced 85 total crashes, a 49.1% increase from the 57 crashes recorded in January 2021. This period saw a rise in total injuries from 22 to 27, while fatalities remained at zero for both years. The most significant year-over-year shift was the overall rise in total crashes by 49.1%.
85
▲ 49.1%was 57
Total Crash Events
0
Persons Killed
27
▲ 22.7%was 22
Persons Injured
2
▼ -33.3%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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in CHELSEA, MA showed an upward trend from January 2021 to January 2022. Total crashes increased by 28, representing a 49.1% rise, while total injuries rose from 22 to 27, a 22.7% increase. Fatalities remained at zero for both periods.
2
Hit-and-Run Crashes — January 2022
▼ -33.3% vs prior (3)
Hit-and-run crashes decreased from 3 incidents in January 2021 to 2 incidents in January 2022. Consequently, the hit-and-run crash rate decreased from 5.3% in the prior period to 2.4% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
5
Pedestrians Injured
22
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted between the two periods. In January 2021, the peak day for crashes was Saturday with 13 incidents, and the peak hour was 5 p.m. with 6 crashes. In contrast, January 2022 saw Monday and Thursday as the peak days with 15 crashes each, and the peak hour shifted to 4 p.m. with 9 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes changed year-over-year, though total fatalities remained at zero in both January 2021 and January 2022. Serious injuries increased from 1 in the prior period to 3 in the current period, and minor injuries rose from 6 to 11. Possible injuries decreased slightly from 11 to 9, contributing to an overall increase in total injuries from 22 to 27.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Most severe injury per crash record
Top Contributing Factors
Comparing contributing factors, 'No improper driving' increased by 4 incidents, from 17 in January 2021 to 21 in January 2022. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 4 incidents to 1. Factors such as 'Followed too closely' and 'Failed to yield right of way' also saw increases in their crash counts, rising from 1 to 3 and 1 to 2 respectively.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Under clear weather conditions, crashes increased from 41 in January 2021 to 56 in January 2022, while crashes during snow conditions rose from 5 to 9. Regarding lighting, crashes during daylight hours increased from 24 to 42, and crashes in dark-lighted roadway conditions rose from 32 to 35. On road surfaces, crashes on dry roads increased from 42 to 54, and crashes on wet surfaces doubled from 6 to 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 142 in January 2021 to 195 in January 2022, and total vehicles involved rose from 120 to 159. Honda vehicles were involved in 36 crashes in the current period, up from 20 in the prior period, surpassing Toyota as the most frequently involved make. The 26-34 age group saw the largest increase in persons involved, rising from 30 to 44.
Top Vehicle Makes (159 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Vehicle unit records
22 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (166 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased from 43 in January 2021 to 51 in January 2022. Crashes in 35 mph zones more than doubled, rising from 3 to 7 incidents, and crashes in 55 mph zones increased from 1 to 4. All reported crashes in both periods occurred without any fatalities within these speed zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-01-31 · 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: 2022-01-01 through 2022-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-01-31 (31 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 85
- Total persons involved: 195
- Total vehicles involved: 159
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: January 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/january-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: 2022-01-01 – 2022-01-31
Generated: June 21, 2026 · All rights reserved