Monthly Traffic Safety Analysis

137 CRASHES IN
FITCHBURG, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes in Fitchburg increased from 125 in December 2023 to 137 in December 2024, marking a 9.6% rise year-over-year. The most significant shift was a 72.7% increase in hit-and-run crashes, rising from 11 to 19 incidents.

137

9.6%was 125

Total Crash Events

0

Persons Killed

31

14.8%was 27

Persons Injured

19

72.7%was 11

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. 16 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 incidents in Fitchburg showed an upward trend, increasing by 9.6% from 125 crashes in December 2023 to 137 crashes in December 2024. This indicates a notable rise in crash activity compared to the previous year.

19

Hit-and-Run Crashes — December 2024

72.7% vs prior (11)

Hit-and-run crashes increased significantly year-over-year, rising by 72.7% from 11 incidents in December 2023 to 19 in December 2024. Consequently, the hit-and-run rate increased by 5.1 percentage points, from 8.8% to 13.9%.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

31

Motorists Injured

Prior: 2619.2%

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 from Saturday in December 2023, with 24 incidents, to Friday in December 2024, with 29 incidents. The peak hour remained consistent at 2 PM for both periods, recording 14 crashes in both December 2023 and 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

While both periods reported zero fatalities, total injuries increased by 14.8% from 27 in December 2023 to 31 in December 2024. The count of minor injury crashes (severity B) remained relatively stable, increasing from 14 to 15, while possible injury crashes (severity C) decreased from 7 to 4. December 2023 also reported 2 serious injury crashes (severity A), which were not present in December 2024.

Outcome by Severity (Crash Events)

Minor Injury15minor injury crashes10.9%
7.1%prior 14
Possible Injury4possible injury crashes2.9%
-42.9%prior 7
No Injury102no injury crashes74.5%
9.7%prior 93

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

Inattention as a contributing factor saw a 100% increase in count, rising from 16 in December 2023 to 32 in December 2024. Conversely, crashes attributed to "Followed too closely" decreased by 50% in count, from 14 to 7. There was also a 200% increase in the count of crashes involving "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner," rising from 3 to 9 incidents.

Officer-Reported Primary Contributing Cause

Inattention32 (23.4%)100.0%prior 16
No improper driving26 (19%)-10.3%prior 29
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner9 (6.6%)
Followed too closely7 (5.1%)-50.0%prior 14
Other improper action6 (4.4%)-33.3%prior 9
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway6 (4.4%)
Failed to yield right of way5 (3.6%)-37.5%prior 8
Failure to keep in proper lane or running off road5 (3.6%)0.0%prior 5
Disregarded traffic signs, signals, road markings3 (2.2%)
Made an improper turn2 (1.5%)

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 "Daylight" conditions increased from 70 in December 2023 to 84 in December 2024, while "Dark - lighted roadway" crashes decreased from 35 to 30. There was a notable increase in crashes on "Ice" road surfaces, rising from 4 in December 2023 to 14 in December 2024. Additionally, crashes reported under "Snow" weather conditions increased from 0 in December 2023 to 9 in December 2024.

Weather

Clear88 (64.2%)
-7.4%prior 95
Cloudy14 (10.2%)
27.3%prior 11
Snow9 (6.6%)
Rain9 (6.6%)
12.5%prior 8
Clear/Clear3 (2.2%)
Sleet, hail (freezing rain or drizzle)2 (1.5%)
Snow/Blowing sand, snow2 (1.5%)
Cloudy/Rain2 (1.5%)
Snow/Clear1 (0.7%)
Clear/Cloudy1 (0.7%)

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

Lighting

Daylight84 (61.3%)
20.0%prior 70
Dark - lighted roadway30 (21.9%)
-14.3%prior 35
Dark - roadway not lighted12 (8.8%)
20.0%prior 10
Dawn7 (5.1%)
Dusk3 (2.2%)
-40.0%prior 5
Other1 (0.7%)

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

Road Surface

Dry91 (66.4%)
-8.1%prior 99
Wet22 (16.1%)
4.8%prior 21
Ice14 (10.2%)
Snow10 (7.3%)

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 by 3.36%, from 238 in December 2023 to 246 in December 2024. TOYOTA became the top vehicle make involved in crashes, rising from 31 to 35, while FORD dropped from the top spot (32) to third (21). Among persons involved, the age groups 26-34 and 35-44 both saw increases of 6 and 8 individuals respectively, while the 21-25 and 45-54 age groups each saw an 8-person decrease.

Top Vehicle Makes (246 vehicles)

1
TOYOTA35 (14.2%)
12.9%prior 31
2
HONDA30 (12.2%)
57.9%prior 19
3
FORD21 (8.5%)
-34.4%prior 32
4
CHEVROLET17 (6.9%)
-22.7%prior 22
5
JEEP16 (6.5%)
77.8%prior 9
6
NISSAN15 (6.1%)
-25.0%prior 20
7
SUBARU14 (5.7%)
40.0%prior 10
8
HYUNDAI10 (4.1%)
-33.3%prior 15
9
ACURA8 (3.3%)
33.3%prior 6
10
MERCEDES-BENZ6 (2.4%)

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

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

Sex Distribution (246 persons with recorded sex)

Male135 (54.9%)
-3.6%prior 140
Female111 (45.1%)
5.7%prior 105

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 25 mph speed zones increased by 20 incidents, from 54 in December 2023 to 74 in December 2024. Crashes in 30 mph zones decreased by 5 incidents, from 29 to 24. No fatalities were reported in any speed zone for 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: FITCHBURG, MA
  • Total crash records analyzed: 137
  • Total persons involved: 292
  • Total vehicles involved: 246

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). "FITCHBURG, 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/fitchburg/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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Fitchburg, MA Crash Report — December 2024 | ThatCarHitMe.com