Monthly Traffic Safety Analysis

52 CRASHES IN
SWANSEA, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes decreased slightly from 53 in December 2023 to 52 in December 2024, representing a 1.9% reduction. The most notable year-over-year shift was a substantial increase in hit-and-run crashes. Fatalities remained at zero in both periods.

52

-1.9%was 53

Total Crash Events

0

Persons Killed

16

-11.1%was 18

Persons Injured

6

500.0%was 1

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. 1 crash with unreported severity is 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, the total number of crashes remained relatively stable, with a minor decrease of 1.9% from 53 crashes in December 2023 to 52 crashes in December 2024. Fatalities remained at zero in both periods, while total injuries decreased from 18 to 16.

6

Hit-and-Run Crashes — December 2024

500.0% vs prior (1)

Hit-and-run crashes increased substantially from 1 in December 2023 to 6 in December 2024. This resulted in the hit-and-run crash rate rising from 1.9% of total crashes in the prior period to 11.5% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 18-11.1%

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 peak day for crashes shifted, with December 2023 recording 13 crashes on Friday, while December 2024 had 11 crashes on both Thursday and Friday. The peak hour for crashes remained consistent at 5 PM in both periods, with 9 crashes in December 2023 and 10 crashes in December 2024.

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. There was an increase in serious injury crashes, with 1 serious injury reported in December 2024 compared to none in December 2023. Minor injury crashes decreased from 11 to 8, while possible injury crashes increased from 3 to 5.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.9%
Minor Injury8minor injury crashes15.4%
-27.3%prior 11
Possible Injury5possible injury crashes9.6%
66.7%prior 3
No Injury37no injury crashes71.2%
-2.6%prior 38

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

Crashes attributed to 'Failed to yield right of way' saw a significant decrease, dropping from 16 counts in December 2023 to 5 counts in December 2024, a 68.8% reduction. Conversely, 'No improper driving' crashes increased by 1 count, from 12 to 13, representing an 8.3% rise. 'Followed too closely' crashes decreased by 2 counts, from 8 to 6, a 25% reduction.

Officer-Reported Primary Contributing Cause

No improper driving13 (25%)8.3%prior 12
Followed too closely6 (11.5%)-25.0%prior 8
Failure to keep in proper lane or running off road5 (9.6%)
Failed to yield right of way5 (9.6%)-68.8%prior 16
Inattention4 (7.7%)-20.0%prior 5
Other improper action3 (5.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.8%)
Made an improper turn2 (3.8%)
Distracted2 (3.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.8%)

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

Crashes occurring in 'Clear' weather decreased by 11 counts, from 42 in December 2023 to 31 in December 2024. There was a notable increase in crashes during 'Snow' conditions, rising from 0 in the prior period to 6 in the current period. Crashes in 'Daylight' decreased by 9 counts, from 26 to 17, while those in 'Dark - lighted roadway' increased by 7 counts, from 20 to 27.

Weather

Clear31 (60.8%)
-26.2%prior 42
Snow6 (11.8%)
Clear/Cloudy4 (7.8%)
Cloudy/Rain3 (5.9%)
Rain2 (3.9%)
Cloudy1 (2.0%)
Rain/Cloudy1 (2.0%)
Rain/Severe crosswinds1 (2.0%)
Clear/Rain1 (2.0%)
Snow/Rain1 (2.0%)

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

Lighting

Dark - lighted roadway27 (52.9%)
35.0%prior 20
Daylight17 (33.3%)
-34.6%prior 26
Dark - roadway not lighted7 (13.7%)
16.7%prior 6

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

Road Surface

Dry35 (68.6%)
-18.6%prior 43
Wet9 (17.6%)
-10.0%prior 10
Snow5 (9.8%)
Ice1 (2.0%)
Water (standing, moving)1 (2.0%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased slightly from 93 in December 2023 to 97 in December 2024, a 4.3% rise. Toyota remained the top make involved in crashes, though its count decreased from 15 to 13. Kia and Hyundai saw significant increases in crash involvement, with Kia rising from 3 to 7 crashes and Hyundai from 3 to 6 crashes.

Top Vehicle Makes (97 vehicles)

1
TOYOTA13 (13.4%)
-13.3%prior 15
2
FORD10 (10.3%)
-23.1%prior 13
3
HONDA8 (8.2%)
14.3%prior 7
4
NISSAN7 (7.2%)
16.7%prior 6
5
KIA7 (7.2%)
6
HYUNDAI6 (6.2%)
7
ACURA4 (4.1%)
8
CHEVROLET4 (4.1%)
-55.6%prior 9
9
JEEP4 (4.1%)
-55.6%prior 9
10
MERCEDES-BENZ4 (4.1%)

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

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

Sex Distribution (93 persons with recorded sex)

Male54 (58.1%)
-22.9%prior 70
Female39 (41.9%)
-13.3%prior 45

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

Crashes occurring in 50 mph zones saw the largest proportional increase, rising from 2 in December 2023 to 7 in December 2024, a 250% increase. Conversely, crashes in 45 mph zones decreased by 4 counts, from 8 to 4, a 50% reduction. Crashes in 10 mph and 25 mph zones also decreased by 2 counts each.

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: SWANSEA, MA
  • Total crash records analyzed: 52
  • Total persons involved: 107
  • Total vehicles involved: 97

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). "SWANSEA, 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/swansea/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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Swansea, MA Crash Report — December 2024 | ThatCarHitMe.com