ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · SEPTEMBER 2024
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/september-2024-report
Monthly Traffic Safety Analysis
72 CRASHES IN
CHELSEA, MA
SEPTEMBER 2024
In September 2024, Chelsea recorded 72 total crashes, a decrease from the 95 crashes reported in September 2023. This represents a 24.2% reduction in overall crash incidents year-over-year. A notable shift includes a 125% increase in pedestrian crashes, rising from 4 in the prior period to 9 in the current period.
72
▼ -24.2%was 95
Total Crash Events
0
Persons Killed
25
▼ -7.4%was 27
Persons Injured
5
▼ -16.7%was 6
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 · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, Chelsea experienced a downward trend in total crashes, decreasing by 24.2% from 95 incidents in September 2023 to 72 in September 2024. Total injuries also saw a slight decrease of 7.4%, from 27 to 25. The number of fatalities remained stable at zero for both periods.
5
Hit-and-Run Crashes — September 2024
▼ -16.7% vs prior (6)
The number of hit-and-run crashes decreased from 6 in September 2023 to 5 in September 2024. However, the hit-and-run rate as a percentage of total crashes increased slightly from 6.3% in the prior period to 6.9% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
9
Pedestrians Injured
2
Cyclists Injured
14
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 Friday in September 2023, which had 19 crashes, to Wednesday and Sunday in September 2024, both with 13 crashes. The peak hour remained 3 PM for both periods, though the count decreased from 11 crashes in September 2023 to 9 crashes in September 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both September 2023 and September 2024. While total injuries decreased slightly from 27 to 25, the proportion of injury crashes increased. Serious injuries rose from 1 crash (1.1% share) to 2 crashes (2.8% share), minor injuries from 11 crashes (11.6% share) to 12 crashes (16.7% share), and possible injuries from 6 crashes (6.3% share) to 9 crashes (12.5% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable changes in crash counts year-over-year. Crashes attributed to 'No improper driving' decreased from 26 to 22, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 6 to 2 crashes. Conversely, 'Disregarded traffic signs, signals, road markings' increased from 1 to 4 crashes, and 'Exceeded authorized speed limit' increased from 1 to 2 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 69 to 51, and those in 'Rain' decreased from 10 to 5. Similarly, crashes under 'Daylight' conditions fell from 66 to 52, and those in 'Dark - lighted roadway' conditions decreased from 25 to 20. Crashes on 'Dry' road surfaces decreased from 78 to 60, while those on 'Wet' surfaces decreased from 17 to 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 192 to 136. While Honda and Toyota remained among the top vehicle makes, their involvement counts decreased significantly from 43 to 15 and 36 to 27, respectively. The age group 0-15 saw an increase in persons involved from 9 to 15, while most other age groups, particularly 16-20 and 21-25, experienced decreases in involvement.
Top Vehicle Makes (136 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (162 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both periods occurred in 25 MPH speed zones, though the count decreased from 69 crashes in September 2023 to 53 crashes in September 2024. Crashes in 20 MPH zones also decreased from 8 to 4. Conversely, crashes in 35 MPH zones increased from 3 to 5, and a new 50 MPH zone recorded 1 crash in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-09-01 through 2024-09-30 (30 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 72
- Total persons involved: 182
- Total vehicles involved: 136
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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/september-2024-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: 2024-09-01 – 2024-09-30
Generated: June 21, 2026 · All rights reserved