ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · MARCH 2023
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/march-2023-report
Monthly Traffic Safety Analysis
91 CRASHES IN
CHELSEA, MA
MARCH 2023
Total crashes in Chelsea increased by 46.8%, from 62 in March 2022 to 91 in March 2023. This period saw a significant rise in total injuries, increasing by 52%, from 25 to 38. The most notable year-over-year shift was in DUI crashes, which rose from 0 in March 2022 to 6 in March 2023.
91
▲ 46.8%was 62
Total Crash Events
0
Persons Killed
38
▲ 52.0%was 25
Persons Injured
4
▲ 100.0%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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a substantial increase in crash activity year-over-year, with total crashes rising by 46.8% from 62 to 91. Concurrently, total injuries experienced a 52% increase, moving from 25 to 38. Fatalities remained at zero in both March 2022 and March 2023.
4
Hit-and-Run Crashes — March 2023
▲ 100.0% vs prior (2)
Hit-and-run crashes increased by 100%, from 2 in March 2022 to 4 in March 2023. The hit-and-run rate also increased, rising from 3.2% of total crashes in March 2022 to 4.4% in March 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
5
Pedestrians Injured
2
Cyclists Injured
31
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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 Thursday in March 2022 (15 crashes) to Wednesday in March 2023 (16 crashes). The peak hour also changed, moving from 4 p.m. in March 2022 (7 crashes) to 8 a.m. in March 2023 (10 crashes). Crashes on Wednesday saw a notable increase from 7 to 16, while Thursday saw a slight decrease from 15 to 14 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either March 2022 or March 2023. Serious injury crashes (severity A) decreased from 3 (4.8% of crashes) to 2 (2.2% of crashes). Minor injury crashes (severity B) increased in count from 8 to 17, and as a share of total crashes from 12.9% to 18.7%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record
Top Contributing Factors
The count of crashes attributed to 'No improper driving' significantly increased from 13 in March 2022 to 34 in March 2023, representing a 161.5% rise. Crashes linked to 'Other improper action' rose from 3 to 7, while 'Inattention' increased from 1 to 5 crashes. Conversely, crashes due to 'Failed to yield right of way' decreased from 4 to 2, and 'Disregarded traffic signs, signals, road markings' dropped from 3 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 49 to 68, a 38.8% rise. Crashes during 'Rain' increased from 3 to 8, and 'Cloudy' conditions saw an increase from 2 to 5 crashes. For lighting conditions, 'Daylight' crashes rose from 38 to 55, while crashes in 'Dark - lighted roadway' conditions increased from 20 to 26.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 73.6%, from 110 to 191 year-over-year. Toyota remained the top make involved, increasing from 33 to 56 vehicles, while Honda decreased from 31 to 26 vehicles. All age groups saw an increase in persons involved, with the 45-54 age group increasing from 16 to 39 persons, and the 65+ age group rising from 4 to 15 persons.
Top Vehicle Makes (191 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records
39 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (214 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events
Speed Limit Zones
The 25 mph speed zone continued to account for the highest number of crashes in both periods, increasing from 48 to 60 crashes. Crashes in the 35 mph speed zone increased from 6 to 9. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-03-01 through 2023-03-31 (31 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 91
- Total persons involved: 256
- Total vehicles involved: 191
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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/march-2023-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: 2023-03-01 – 2023-03-31
Generated: June 21, 2026 · All rights reserved