Monthly Traffic Safety Analysis

27 CRASHES IN
LITTLETON, MA
JANUARY 2024

All metrics benchmarked againstJanuary 2023

Total crashes in January 2024 increased to 27, up from 26 in January 2023, representing a 3.85% rise. The most notable year-over-year shift was a significant decrease in total injuries, which fell by 42.86% from 7 to 4.

27

3.8%was 26

Total Crash Events

1

Persons Killed

4

-42.9%was 7

Persons Injured

1

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2024-01-01 to 2024-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Littleton showed a slight upward trend, with total crashes increasing by 3.85% year-over-year from 26 to 27. Despite this increase in crash volume, the number of injuries decreased substantially, while fatalities remained stable.

1

Hit-and-Run Crashes — January 2024

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 for both January 2023 and January 2024. The hit-and-run rate slightly decreased from 3.8% in January 2023 to 3.7% in January 2024.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 10.0%

4

Motorists Injured

Prior: 7-42.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-01-31 · 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 Friday in January 2023 (7 crashes) to Sunday in January 2024 (8 crashes). The peak hour for crashes remained consistent at 6 p.m. for both periods, with 3 crashes occurring at that hour in both January 2023 and January 2024.

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

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

Crash Severity Breakdown

The fatal crash rate slightly decreased from 3.85% in January 2023 to 3.7% in January 2024, with one fatal crash recorded in both periods. The proportion of serious injury crashes increased from 0% in January 2023 to 3.7% in January 2024, corresponding to one serious injury crash. Possible injury crashes decreased from 3 (11.5%) to 1 (3.7%) year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.7%
0.0%prior 1
Serious Injury1serious injury crashes3.7%
Minor Injury2minor injury crashes7.4%
0.0%prior 2
Possible Injury1possible injury crashes3.7%
-66.7%prior 3
No Injury21no injury crashes77.8%
10.5%prior 19

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

Crashes attributed to 'No improper driving' increased by 2, from 6 in January 2023 to 8 in January 2024. 'Driving too fast for conditions' crashes increased by 1, from 2 to 3. Conversely, 'Inattention' crashes decreased by 1, from 3 to 2, and 'Over-correcting/over-steering' crashes also decreased by 1, from 3 to 2.

Officer-Reported Primary Contributing Cause

No improper driving8 (29.6%)33.3%prior 6
Driving too fast for conditions3 (11.1%)
Inattention2 (7.4%)
Over-correcting/over-steering2 (7.4%)
Followed too closely2 (7.4%)
Visibility obstructed1 (3.7%)
Failed to yield right of way1 (3.7%)
Disregarded traffic signs, signals, road markings1 (3.7%)
Glare1 (3.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.7%)

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

Road & Environmental Conditions

The number of crashes occurring in 'Daylight' conditions increased from 15 in January 2023 to 18 in January 2024. Crashes on 'Wet' road surfaces increased from 5 to 8 year-over-year, while crashes on 'Dry' road surfaces slightly decreased from 13 to 12. There was no change in the number of crashes occurring in 'Clear' or 'Snow' weather conditions.

Weather

Clear10 (37.0%)
0.0%prior 10
Snow6 (22.2%)
0.0%prior 6
Cloudy4 (14.8%)
Cloudy/Snow2 (7.4%)
Rain2 (7.4%)
Snow/Sleet, hail (freezing rain or drizzle)1 (3.7%)
Clear/Cloudy1 (3.7%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (3.7%)

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

Lighting

Daylight18 (66.7%)
20.0%prior 15
Dark - lighted roadway4 (14.8%)
Dark - roadway not lighted4 (14.8%)
-33.3%prior 6
Dusk1 (3.7%)

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

Road Surface

Dry12 (44.4%)
-7.7%prior 13
Wet8 (29.6%)
60.0%prior 5
Snow6 (22.2%)
0.0%prior 6
Slush1 (3.7%)

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

Vehicles & Demographics

Top Vehicle Makes (42 vehicles)

1
HONDA6 (14.3%)
2
TOYOTA5 (11.9%)
-37.5%prior 8
3
NISSAN5 (11.9%)
4
SUBARU4 (9.5%)
5
FORD4 (9.5%)
6
JEEP3 (7.1%)
7
FRHT2 (4.8%)
8
MERCEDES-BENZ1 (2.4%)
9
MITS1 (2.4%)
10
TESLA1 (2.4%)

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

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

Sex Distribution (48 persons with recorded sex)

Male30 (62.5%)
15.4%prior 26
Female18 (37.5%)
63.6%prior 11

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

Speed Limit Zones

Crashes in the 35 MPH speed limit zone saw a substantial increase from 1 in January 2023 to 9 in January 2024, with one fatal crash occurring in this zone in the current period. Conversely, crashes in the 25 MPH speed limit zone decreased from 9 to 2. The fatal crash in January 2023 occurred in a 45 MPH zone, which saw no fatal crashes in the current period.

Fatal crashes by zone: 35 mph: 1 of 9 (11.111%)

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

Data Coverage

  • Reporting period: 2024-01-01 through 2024-01-31 (31 days)
  • Geographic scope: LITTLETON, MA
  • Total crash records analyzed: 27
  • Total persons involved: 50
  • Total vehicles involved: 42

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). "LITTLETON, MA Crash Intelligence Report: January 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/littleton/january-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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Littleton, MA Crash Report — January 2024 | ThatCarHitMe.com