Monthly Traffic Safety Analysis

206 CRASHES IN
QUINCY, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, Quincy experienced 206 crashes, a decrease from 223 crashes in December 2023, representing a 7.6% reduction. Total injuries also decreased from 71 to 46, a 35.2% reduction. A notable shift was observed in hit-and-run crashes, which decreased by 36.1% year-over-year.

206

-7.6%was 223

Total Crash Events

0

Persons Killed

46

-35.2%was 71

Persons Injured

23

-36.1%was 36

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for December 2024 in Quincy shows a downward trend compared to December 2023. Total crashes decreased by 7.6%, from 223 to 206. Additionally, total injuries saw a significant reduction of 35.2%, falling from 71 to 46.

23

Hit-and-Run Crashes — December 2024

-36.1% vs prior (36)

Hit-and-run incidents significantly decreased in December 2024 compared to the prior year. The number of hit-and-run crashes fell from 36 to 23, representing a 36.1% reduction. Consequently, the hit-and-run rate decreased from 16.1% of all crashes in December 2023 to 11.2% in December 2024, indicating a positive trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

5

Pedestrians Injured

Prior: 425.0%

39

Motorists Injured

Prior: 65-40.0%

2

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 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 year-over-year. In December 2023, the peak day for crashes was Friday with 52 incidents, and the peak hour was 10a with 20 incidents. In December 2024, the peak day shifted to Tuesday with 44 crashes, and the peak hour moved to 3p with 19 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both December 2023 and December 2024. The proportion of crashes resulting in injury decreased, with minor injuries falling from 38 (17% of crashes) to 27 (13.1% of crashes) and possible injuries decreasing from 18 (8.1% of crashes) to 10 (4.9% of crashes). Conversely, crashes with no injury increased from 152 (68.2% of crashes) to 158 (76.7% of crashes).

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes1.5%
0.0%prior 3
Minor Injury27minor injury crashes13.1%
-28.9%prior 38
Possible Injury10possible injury crashes4.9%
-44.4%prior 18
No Injury158no injury crashes76.7%
3.9%prior 152

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' remained the most frequent, decreasing slightly from 62 incidents in December 2023 to 60 in December 2024. 'Failed to yield right of way' saw a significant decrease of 13 incidents, falling from 32 to 19, and dropped from the second to the fourth most common factor. Conversely, 'Followed too closely' increased by 4 incidents, from 16 to 20, moving from the fourth to the third most common factor.

Officer-Reported Primary Contributing Cause

Inattention60 (29.1%)-3.2%prior 62
No improper driving25 (12.1%)-7.4%prior 27
Followed too closely20 (9.7%)25.0%prior 16
Failed to yield right of way19 (9.2%)-40.6%prior 32
Disregarded traffic signs, signals, road markings9 (4.4%)80.0%prior 5
Other improper action6 (2.9%)
Glare5 (2.4%)0.0%prior 5
Driving too fast for conditions4 (1.9%)-33.3%prior 6
Failure to keep in proper lane or running off road4 (1.9%)-60.0%prior 10
Physical impairment4 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crash conditions showed some changes. Crashes occurring in 'Clear' or 'Clear/Clear' weather conditions remained stable at 141 incidents in both periods, while incidents in 'Rain', 'Snow', 'Sleet', or 'Fog' conditions decreased from 43 to 30. Regarding road surface, the number of crashes on 'Dry' roads decreased from 163 to 142, while crashes on 'Wet', 'Snow', 'Ice', or 'Slush' surfaces collectively increased from 59 to 62. Crashes occurring in 'Dark' conditions (lighted or unlighted) decreased from 109 in December 2023 to 88 in December 2024.

Weather

Clear109 (53.2%)
-10.7%prior 122
Clear/Clear32 (15.6%)
68.4%prior 19
Rain15 (7.3%)
-55.9%prior 34
Cloudy11 (5.4%)
-60.7%prior 28
Rain/Cloudy4 (2.0%)
-20.0%prior 5
Rain/Rain4 (2.0%)
Snow3 (1.5%)
Sleet, hail (freezing rain or drizzle)3 (1.5%)
Clear/Cloudy3 (1.5%)
Cloudy/Cloudy3 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight116 (56.3%)
11.5%prior 104
Dark - lighted roadway81 (39.3%)
-13.8%prior 94
Dark - roadway not lighted5 (2.4%)
-28.6%prior 7
Other1 (0.5%)
Dawn1 (0.5%)
-80.0%prior 5
Dark - unknown roadway lighting1 (0.5%)
Dusk1 (0.5%)
-85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry142 (69.3%)
-12.9%prior 163
Wet42 (20.5%)
-27.6%prior 58
Snow9 (4.4%)
Ice7 (3.4%)
Slush4 (2.0%)
Sand, mud, dirt, oil, gravel1 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Toyota remained the most frequently involved vehicle make, with its count increasing from 81 in December 2023 to 91 in December 2024. Honda involvement decreased from 63 to 53, while Jeep saw a 50% increase in involvement, from 16 to 24. In terms of person age distribution, individuals aged 26-34 and 65+ saw increases in their representation in crashes, rising by 13 counts each, to 103 and 63 respectively. Conversely, persons aged 0-15 and 55-64 experienced notable decreases, with counts falling by 8 and 18 respectively.

Top Vehicle Makes (406 vehicles)

1
TOYOTA91 (22.4%)
12.3%prior 81
2
HONDA53 (13.1%)
-15.9%prior 63
3
FORD37 (9.1%)
-9.8%prior 41
4
NISSAN30 (7.4%)
7.1%prior 28
5
JEEP24 (5.9%)
50.0%prior 16
6
CHEVROLET19 (4.7%)
-42.4%prior 33
7
LEXUS18 (4.4%)
125.0%prior 8
8
SUBARU16 (3.9%)
60.0%prior 10
9
MERCEDES-BENZ11 (2.7%)
37.5%prior 8
10
HYUNDAI11 (2.7%)
-8.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (458 persons with recorded sex)

Male265 (57.9%)
2.3%prior 259
Female193 (42.1%)
-2.0%prior 197

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones remained largely consistent year-over-year. Crashes in 25 mph zones saw a slight increase from 141 to 142 incidents. Conversely, crashes in 55 mph zones decreased from 22 to 21, and incidents in 30 mph zones decreased from 18 to 16. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: QUINCY, MA
  • Total crash records analyzed: 206
  • Total persons involved: 510
  • Total vehicles involved: 406

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/quincy/december-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

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Quincy, MA Crash Report — December 2024 | ThatCarHitMe.com