ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHELSEA, MA · 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/2024-annual-report
Yearly Traffic Safety Analysis
980 CRASHES IN
CHELSEA, MA
2024
In 2024, Chelsea recorded 980 total traffic crashes, a 6.8% decrease from the 1,051 crashes in 2023. While overall crashes declined, the number of fatal crashes increased from 2 to 3. One of the most notable shifts was a 40% increase in crashes involving pedestrians, which rose from 35 in 2023 to 49 in 2024.
980
▼ -6.8%was 1,051
Total Crash Events
3
▲ 50.0%was 2
Persons Killed
358
▲ 2.6%was 349
Persons Injured
41
▼ -25.5%was 55
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 13 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Chelsea decreased by 6.8% from 1,051 incidents in 2023 to 980 in 2024. Despite the drop in total crashes, the number of people injured rose slightly by 2.6% from 349 to 358. Fatalities also increased, with 3 individuals killed in 2024 compared to 2 in the prior year.
41
Hit-and-Run Crashes — 2024
▼ -25.5% vs prior (55)
Hit-and-run incidents decreased from 2023 to 2024. The total number of hit-and-run crashes fell from 55 to 41. The hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also trended down, declining from 5.2% in 2023 to 4.2% in 2024.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
41
Pedestrians Injured
12
Cyclists Injured
297
Motorists Injured
8
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Saturday (183 crashes) in 2023 to Thursday (159 crashes) in 2024. Similarly, the peak hour for collisions shifted one hour earlier, from the 4 p.m. hour in 2023 (86 crashes) to the 3 p.m. hour in 2024 (84 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, their severity profile shifted year-over-year. The number of fatal crashes increased from 2 to 3, and the fatal crash rate rose from 0.19% to 0.31%. The proportion of crashes resulting in minor injuries grew from 10.8% (113 crashes) of all incidents in 2023 to 15.5% (152 crashes) in 2024. Consequently, the share of crashes with no reported injuries fell from 73.9% to 71.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained broadly consistent, with 'No improper driving' being the most common finding in both years, though its count fell from 369 to 324. The count for crashes attributed to 'Disregarded traffic signs, signals, road markings' saw a notable 66.7% increase, rising from 12 incidents in 2023 to 20 in 2024. Conversely, crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from a count of 38 to 28.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained largely stable year-over-year, with the majority of incidents in both periods occurring in daylight and on dry roads. In 2024, 84.1% of crashes happened on dry surfaces, compared to 82.6% in 2023. There was a slight decrease in the proportion of crashes occurring in adverse weather, with crashes during rain accounting for 5.9% of the total in 2024, down from 7.5% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The demographic profile of vehicles and persons involved in crashes showed little change year-over-year. Toyota, Honda, and Ford were the top three vehicle makes involved in crashes in both 2023 and 2024, with their counts decreasing in line with the overall drop in total vehicles. The age distribution of persons involved also remained consistent, with the 26-34 age group representing the largest cohort in both years, accounting for 20.9% of persons in 2023 and 20.3% in 2024.
Top Vehicle Makes (1,948 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
269 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,210 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The concentration of crashes in 25 mph zones increased in 2024. While the absolute number of crashes in these zones was stable (771 in 2024 vs. 767 in 2023), they accounted for a larger share of the total, rising from 73.0% in 2023 to 78.7% in 2024. Both years saw 2 fatal crashes in 25 mph zones; however, 2024 recorded an additional fatality in a 50 mph zone, a speed zone that had no fatal crashes in the prior year.
Fatal crashes by zone: 25 mph: 2 of 771 (0.259%) · 50 mph: 1 of 19 (5.263%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: CHELSEA, MA
- Total crash records analyzed: 980
- Total persons involved: 2,500
- Total vehicles involved: 1,948
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chelsea/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved