ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · QUINCY, 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/quincy/2024-annual-report
Yearly Traffic Safety Analysis
2,239 CRASHES IN
QUINCY, MA
2024
In 2024, Quincy recorded 2,239 vehicle crashes, a 4.0% increase from the 2,153 crashes recorded in 2023. Total injuries increased slightly from 569 to 577, while fatalities decreased from 3 to 2. A notable year-over-year shift was the 80% increase in crashes involving bicycles, which rose from 15 to 27.
2,239
▲ 4.0%was 2,153
Total Crash Events
2
▼ -33.3%was 3
Persons Killed
577
▲ 1.4%was 569
Persons Injured
297
▲ 18.8%was 250
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 78 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 traffic collisions in Quincy increased by 4.0% from 2023 to 2024, with 86 more crashes reported. Despite the rise in total crashes, the number of resulting injuries saw a smaller increase of 1.4% (from 569 to 577), and total fatalities decreased from 3 to 2.
297
Hit-and-Run Crashes — 2024
▲ 18.8% vs prior (250)
The number of hit-and-run incidents increased by 18.8% year-over-year, rising from 250 in 2023 to 297 in 2024. This corresponds to an increase in the hit-and-run rate, which grew from 11.6% of all crashes in the prior period to 13.3% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
44
Pedestrians Injured
25
Cyclists Injured
502
Motorists Injured
6
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 showed some changes year-over-year. The peak day for collisions shifted from Friday (355 crashes) in 2023 to Tuesday (367 crashes) in 2024. The peak hour remained consistent at 5 p.m. in both periods, although the number of crashes during that hour increased from 182 to 206.
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 the total number of fatal crashes decreased from 3 to 2, the count of crashes resulting in serious injuries increased by 33.3%, from 24 in 2023 to 32 in 2024. Crashes resulting in minor injuries also rose by 5.4% from 299 to 315. Consequently, the share of crashes involving any injury (Fatal, Serious, Minor, or Possible) increased slightly from 23.3% to 24.2%.
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 top three primary contributing factors remained the same across both periods: 'Inattention,' 'No improper driving,' and 'Failed to yield right of way.' The count of crashes where 'Inattention' was cited as a factor increased by 14.4%, from 638 in 2023 to 730 in 2024. In contrast, crashes where 'No improper driving' was noted decreased from 306 to 285.
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
The majority of crashes in both periods occurred during daylight on dry roads under clear weather. The proportion of crashes on wet roads decreased from 18.9% of all crashes in 2023 to 16.0% in 2024. Similarly, crashes in rainy conditions accounted for a smaller share of the total, dropping from 13.5% to 11.5% year-over-year.
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 age distribution of persons involved in crashes remained largely stable, with the 26-34 age group representing the largest cohort in both years. The number of individuals aged 65 and older involved in crashes increased from 576 to 652. The top three vehicle makes involved in collisions were consistent, with Toyota, Honda, and Ford leading in both 2023 and 2024.
Top Vehicle Makes (4,305 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
559 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,849 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
Crashes predominantly occurred in 25 mph speed zones in both years, with the count in this zone increasing by 11.6% from 1,332 to 1,486. The locations of fatal crashes shifted; in 2024, one fatality occurred in a 20 mph zone and another in a 30 mph zone. This contrasts with 2023, when two fatalities were recorded in a 25 mph zone and one in a 15 mph zone.
Fatal crashes by zone: 20 mph: 1 of 44 (2.273%) · 30 mph: 1 of 219 (0.457%)
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: QUINCY, MA
- Total crash records analyzed: 2,239
- Total persons involved: 5,370
- Total vehicles involved: 4,305
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). "QUINCY, 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/quincy/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