ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · DECEMBER 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/december-2023-report
Monthly Traffic Safety Analysis
92 CRASHES IN
CHELSEA, MA
DECEMBER 2023
In December 2023, Chelsea experienced 92 total crashes, a slight decrease from 93 crashes in December 2022, representing a 1.08% reduction. The most notable shift was the increase in speeding-related crashes, which rose from 0 in the prior period to 2 in the current period. Total injuries also saw a significant decrease year-over-year.
92
▼ -1.1%was 93
Total Crash Events
0
Persons Killed
33
▼ -15.4%was 39
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash frequency in Chelsea remained relatively stable year-over-year, with a minor decrease of 1 crash. However, total injuries decreased more substantially, from 39 in December 2022 to 33 in December 2023, marking a 15.38% reduction. Fatalities remained at zero in both periods.
6
Hit-and-Run Crashes — December 2023
▲ 50.0% vs prior (4)
Hit-and-run crashes increased from 4 incidents in December 2022 to 6 incidents in December 2023. This change led to an increase in the hit-and-run rate, rising from 4.3% of all crashes in the prior period to 6.5% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
32
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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 Sunday with 19 crashes in December 2022 to Saturday with 26 crashes in December 2023. Similarly, the peak hour for crashes moved from 6 PM with 12 crashes in the prior period to 4 PM with 11 crashes in the current period. This indicates a shift in the most crash-prone times.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either December 2022 or December 2023. Serious injuries decreased from 3 in the prior period to 1 in the current period. The proportion of crashes resulting in any injury (Serious, Minor, or Possible) decreased from 32.2% (30 crashes) in December 2022 to 21.7% (20 crashes) in December 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to 'No improper driving' increased from 29 in December 2022 to 32 in December 2023, remaining the most frequent factor. 'Followed too closely' crashes saw a significant increase, rising from 1 to 4 crashes. Conversely, crashes due to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 5 to 2 crashes year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 60 in December 2022 to 66 in December 2023. Crashes on 'Dry' road surfaces also rose from 56 to 70 between the two periods. Conversely, crashes on 'Wet' road surfaces decreased from 26 to 21, and those on 'Ice' decreased from 4 to 1.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes saw a shift in ranking, with Toyota decreasing from 44 to 30 incidents, and Honda decreasing from 36 to 32. The age group with the highest number of involved persons shifted from 26-34 years old (42 persons) in December 2022 to 35-44 years old (54 persons) in December 2023. The total number of persons involved increased from 225 to 234.
Top Vehicle Makes (182 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (213 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone decreased from 73 in December 2022 to 65 in December 2023. Conversely, crashes in the 45 mph speed zone increased from 2 to 5 between the two periods. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-12-01 through 2023-12-31 (31 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 92
- Total persons involved: 234
- Total vehicles involved: 182
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: December 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/december-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: 2023-12-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved