ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · QUINCY, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
2,063 CRASHES IN
QUINCY, MA
2022
In 2022, Quincy recorded 2,063 total vehicle crashes, a 1.7% increase from the 2,029 crashes documented in 2021. While the overall crash volume saw a slight rise, the number of fatalities decreased by 50%, falling from 4 in 2021 to 2 in 2022. Total injuries also declined from 546 to 506 over the same period.
2,063
▲ 1.7%was 2,029
Total Crash Events
2
▼ -50.0%was 4
Persons Killed
506
▼ -7.3%was 546
Persons Injured
239
▲ 5.3%was 227
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. 71 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Quincy show a slight increase year-over-year, with total incidents rising from 2,029 in 2021 to 2,063 in 2022, a 1.7% increase. Despite the rise in total crashes, outcomes became less severe on average. The number of people killed in crashes fell from 4 to 2, and the total number of injuries decreased by 7.3% from 546 to 506.
239
Hit-and-Run Crashes — 2022
▲ 5.3% vs prior (227)
Hit-and-run incidents increased in both count and rate from 2021 to 2022. The number of hit-and-run crashes rose from 227 to 239, representing a 5.3% increase in count. As a proportion of all crashes, the hit-and-run rate also edged up slightly from 11.2% in 2021 to 11.6% in 2022, indicating a minor upward trend.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
50
Pedestrians Injured
12
Cyclists Injured
443
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent between 2021 and 2022. The afternoon commute hour of 5 PM was the peak time for crashes in both years, though the number of crashes during this hour decreased from 182 to 161. The peak day for crashes shifted slightly from Thursday in 2021, with 322 crashes, to Friday in 2022, with 334 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes decreased from 2021 to 2022. The number of fatal crashes was halved, dropping from 4 to 2, which lowered the fatal crash rate from 0.2% to 0.1% of all crashes. Crashes resulting in serious injuries also declined, from 42 (2.1% of total) in 2021 to 31 (1.5%) in 2022. Conversely, the count of crashes involving minor injuries increased from 271 to 291, and property-damage-only crashes rose from 1,539 to 1,585.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
'Inattention' remained the top contributing factor, with the count of related crashes increasing from 602 in 2021 to 637 in 2022. 'Failed to yield right of way' and 'Followed too closely' were also leading factors in both years, though their counts decreased from 250 to 236 and 187 to 183, respectively. Notably, crashes where 'No improper driving' was recorded decreased from 317 to 264.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both 2021 and 2022 occurred in clear weather on dry roads during daylight hours. Crashes on wet roads decreased from 348 to 305, while those on dry roads increased from 1,640 to 1,672. A notable shift was observed in crashes on icy roads, which increased from 5 incidents in 2021 to 38 in 2022. The distribution of crashes by lighting conditions remained stable, with 'Daylight' accounting for the largest share in both years.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The composition of vehicles involved in crashes was consistent year-over-year, with Toyota, Honda, and Ford remaining the top three most frequently involved makes in both 2021 and 2022. Analysis of person age groups shows a notable increase in involvement for the 65+ age group, which grew from 452 individuals in 2021 to 529 in 2022. Conversely, the 26-34 age group, while still the largest, saw its involvement decrease from 1,012 to 963 persons.
Top Vehicle Makes (3,964 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
496 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (4,560 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained highly stable between 2021 and 2022. The 25 mph zone accounted for the highest number of crashes in both years, with an identical count of 1,090. The location of fatal crashes shifted; in 2022, both fatal crashes occurred in a 30 mph zone. This contrasts with 2021, when the 4 fatal crashes were distributed across 25 mph (2), 35 mph (1), and 55 mph (1) zones.
Fatal crashes by zone: 30 mph: 2 of 396 (0.505%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: QUINCY, MA
- Total crash records analyzed: 2,063
- Total persons involved: 5,014
- Total vehicles involved: 3,964
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/quincy/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved