Monthly Traffic Safety Analysis

187 CRASHES IN
QUINCY, MA
JUNE 2022

All metrics benchmarked againstJune 2021

In June 2022, Quincy, MA experienced 187 total crashes, an increase of 12.65% from the 166 crashes recorded in June 2021. Despite this overall increase, hit-and-run incidents saw a notable decrease, falling from 22 crashes in June 2021 to 16 crashes in June 2022.

187

12.7%was 166

Total Crash Events

0

Persons Killed

58

41.5%was 41

Persons Injured

16

-27.3%was 22

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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in total crashes year-over-year, with a rise from 166 crashes in June 2021 to 187 crashes in June 2022. This represents a 12.65% increase in crash incidents during the observed period.

16

Hit-and-Run Crashes — June 2022

-27.3% vs prior (22)

Hit-and-run crashes decreased from 22 in June 2021 to 16 in June 2022, representing a reduction of 6 incidents. The hit-and-run rate also saw a decline, dropping from 13.3% of total crashes in June 2021 to 8.6% in June 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 250.0%

2

Cyclists Injured

Prior: 1100.0%

53

Motorists Injured

Prior: 3839.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 Monday with 31 crashes in June 2021 to Wednesday with 33 crashes in June 2022. The peak hour for crashes remained consistent at 2 p.m. in both periods, with 17 crashes recorded during that hour in both June 2021 and June 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either June 2021 or June 2022. Total injuries increased from 41 in June 2021 to 58 in June 2022. Serious injuries decreased from 5 (3% of crashes) in June 2021 to 3 (1.6% of crashes) in June 2022, while minor injuries increased from 19 (11.4% of crashes) to 30 (16% of crashes).

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1.6%
-40.0%prior 5
Minor Injury30minor injury crashes16%
57.9%prior 19
Possible Injury12possible injury crashes6.4%
50.0%prior 8
No Injury136no injury crashes72.7%
7.9%prior 126

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the top contributing factor, increasing from 45 crashes in June 2021 to 53 crashes in June 2022, an 8-crash increase. Crashes attributed to 'Followed too closely' rose from 21 to 26, a 5-crash increase. Conversely, 'Failed to yield right of way' crashes slightly decreased from 19 to 18.

Officer-Reported Primary Contributing Cause

Inattention53 (28.3%)17.8%prior 45
No improper driving31 (16.6%)6.9%prior 29
Followed too closely26 (13.9%)23.8%prior 21
Failed to yield right of way18 (9.6%)-5.3%prior 19
Failure to keep in proper lane or running off road8 (4.3%)
Disregarded traffic signs, signals, road markings8 (4.3%)33.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (3.2%)
Over-correcting/over-steering4 (2.1%)
Distracted2 (1.1%)
Visibility obstructed2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in daylight conditions increased from 71.1% (118 of 166 crashes) in June 2021 to 78.6% (147 of 187 crashes) in June 2022. Crashes on dry road surfaces decreased proportionally from 91% (151 of 166 crashes) to 88.2% (165 of 187 crashes) year-over-year. Crashes in clear weather conditions also saw a slight proportional decrease from 74.7% (124 of 166 crashes) to 72.2% (135 of 187 crashes).

Weather

Clear135 (72.6%)
8.9%prior 124
Clear/Clear16 (8.6%)
33.3%prior 12
Cloudy16 (8.6%)
14.3%prior 14
Rain11 (5.9%)
37.5%prior 8
Rain/Rain3 (1.6%)
Cloudy/Rain2 (1.1%)
Rain/Cloudy2 (1.1%)
Unknown/Unknown1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight147 (78.6%)
24.6%prior 118
Dark - lighted roadway34 (18.2%)
-8.1%prior 37
Dawn2 (1.1%)
Dusk2 (1.1%)
-66.7%prior 6
Dark - roadway not lighted1 (0.5%)
Other1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Road Surface

Dry165 (89.2%)
9.3%prior 151
Wet20 (10.8%)
53.8%prior 13

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 326 in June 2021 to 365 in June 2022. There was a notable increase of 24 persons in the 55-64 age group involved in crashes, rising from 35 to 59. Toyota remained the top vehicle make involved, increasing from 54 to 70 vehicles, while Chevrolet saw a significant increase from 17 to 31 vehicles involved.

Top Vehicle Makes (365 vehicles)

1
TOYOTA70 (19.2%)
29.6%prior 54
2
HONDA36 (9.9%)
-18.2%prior 44
3
FORD35 (9.6%)
-10.3%prior 39
4
CHEVROLET31 (8.5%)
82.4%prior 17
5
NISSAN29 (7.9%)
61.1%prior 18
6
JEEP19 (5.2%)
-13.6%prior 22
7
HYUNDAI13 (3.6%)
116.7%prior 6
8
SUBARU12 (3.3%)
100.0%prior 6
9
KIA9 (2.5%)
12.5%prior 8
10
DODGE9 (2.5%)
0.0%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

41 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (406 persons with recorded sex)

Male234 (57.6%)
4.9%prior 223
Female172 (42.4%)
8.9%prior 158

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 55 mph speed zones saw a substantial increase, rising from 16 in June 2021 to 33 in June 2022, increasing their proportion from 9.6% to 17.6% of total crashes. Conversely, crashes in 30 mph zones decreased from 38 to 30, and crashes in 25 mph zones slightly decreased from 94 to 93. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: QUINCY, MA
  • Total crash records analyzed: 187
  • Total persons involved: 446
  • Total vehicles involved: 365

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: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/quincy/june-2022-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

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Quincy, MA Crash Report — June 2022 | ThatCarHitMe.com