Monthly Traffic Safety Analysis

125 CRASHES IN
FITCHBURG, MA
DECEMBER 2023

All metrics benchmarked againstDecember 2022

In December 2023, Fitchburg experienced 125 total crashes, marking an 11.35% decrease compared to the 141 crashes reported in December 2022. The most significant year-over-year shift was a substantial increase in hit-and-run crashes, rising from 1 in December 2022 to 11 in December 2023.

125

-11.3%was 141

Total Crash Events

0

Persons Killed

27

12.5%was 24

Persons Injured

11

1000.0%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. 9 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Fitchburg decreased by 11.35% year-over-year, from 141 crashes in December 2022 to 125 crashes in December 2023. Despite this reduction in total crashes, the number of injured persons increased by 12.5%, from 24 in the prior period to 27 in the current period. Fatalities remained at zero in both periods.

11

Hit-and-Run Crashes — December 2023

1000.0% vs prior (1)

Hit-and-run crashes saw a substantial increase, rising from 1 crash in December 2022 to 11 crashes in December 2023. This resulted in the hit-and-run rate climbing from 0.7% of total crashes in the prior period to 8.8% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

26

Motorists Injured

Prior: 2313.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Saturday in both periods, though the count decreased from 31 crashes in December 2022 to 24 crashes in December 2023. The peak hour for crashes shifted from 4 p.m. with 19 crashes in December 2022 to 2 p.m. with 14 crashes in December 2023. Friday also had 24 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either December 2022 or December 2023. The total number of injured persons increased from 24 in December 2022 to 27 in December 2023. Crashes resulting in serious injuries (severity A) doubled from 1 (0.7% of total crashes) in the prior year to 2 (1.6% of total crashes) in the current year.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.6%
100.0%prior 1
Minor Injury14minor injury crashes11.2%
27.3%prior 11
Possible Injury7possible injury crashes5.6%
75.0%prior 4
No Injury93no injury crashes74.4%
-21.8%prior 119

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' saw a significant decrease in count from 65 crashes (46.1% share) in December 2022 to 29 crashes (23.2% share) in December 2023. Conversely, 'Inattention' increased from 11 crashes in the prior period to 16 crashes in the current period, and 'Followed too closely' increased from 11 crashes to 14 crashes.

Officer-Reported Primary Contributing Cause

No improper driving29 (23.2%)-55.4%prior 65
Inattention16 (12.8%)45.5%prior 11
Followed too closely14 (11.2%)27.3%prior 11
Other improper action9 (7.2%)0.0%prior 9
Failed to yield right of way8 (6.4%)-11.1%prior 9
Failure to keep in proper lane or running off road5 (4%)
Distracted4 (3.2%)
Made an improper turn4 (3.2%)-33.3%prior 6
Over-correcting/over-steering3 (2.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 83 in December 2022 to 95 in December 2023. Crashes on 'Dry' road surfaces increased from 73 to 99, while crashes on 'Ice' decreased substantially from 27 to 4, and crashes on 'Snow' road surfaces decreased from 20 to 0.

Weather

Clear95 (76.6%)
14.5%prior 83
Cloudy11 (8.9%)
120.0%prior 5
Rain8 (6.5%)
-20.0%prior 10
Fog, smog, smoke2 (1.6%)
Sleet, hail (freezing rain or drizzle)2 (1.6%)
Cloudy/Rain1 (0.8%)
Clear/Rain1 (0.8%)
Other1 (0.8%)
Clear/Cloudy1 (0.8%)
Snow/Clear1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight70 (56.9%)
-1.4%prior 71
Dark - lighted roadway35 (28.5%)
-23.9%prior 46
Dark - roadway not lighted10 (8.1%)
-28.6%prior 14
Dusk5 (4.1%)
0.0%prior 5
Dawn3 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry99 (79.8%)
35.6%prior 73
Wet21 (16.9%)
16.7%prior 18
Ice4 (3.2%)
-85.2%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 259 in December 2022 to 238 in December 2023. Toyota, the top make in December 2022 with 43 vehicles, saw a decrease to 31 vehicles, while Ford became the top make in December 2023 with 32 vehicles. The age group 0-15 saw a decrease in persons involved from 26 to 11, while the 16-20 age group increased from 18 to 26.

Top Vehicle Makes (238 vehicles)

1
FORD32 (13.4%)
23.1%prior 26
2
TOYOTA31 (13%)
-27.9%prior 43
3
CHEVROLET22 (9.2%)
10.0%prior 20
4
NISSAN20 (8.4%)
17.6%prior 17
5
HONDA19 (8%)
-45.7%prior 35
6
HYUNDAI15 (6.3%)
36.4%prior 11
7
SUBARU10 (4.2%)
-23.1%prior 13
8
JEEP9 (3.8%)
-18.2%prior 11
9
KIA9 (3.8%)
28.6%prior 7
10
MAZDA7 (2.9%)
16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (245 persons with recorded sex)

Male140 (57.1%)
-2.8%prior 144
Female105 (42.9%)
-21.1%prior 133

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed limit zone decreased from 71 in December 2022 to 54 in December 2023. Conversely, crashes in the 30 mph zone increased slightly from 26 to 29. No fatal crashes were recorded in any speed limit zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-12-01 to 2023-12-31 · 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: 2023-12-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-12-01 through 2023-12-31 (31 days)
  • Geographic scope: FITCHBURG, MA
  • Total crash records analyzed: 125
  • Total persons involved: 280
  • Total vehicles involved: 238

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 2023." Published June 21, 2026. Reporting period: 2023-12-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/fitchburg/december-2023-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 2023 | ThatCarHitMe.com