Monthly Traffic Safety Analysis

39 CRASHES IN
LUDLOW, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

In November 2024, Ludlow experienced 39 crashes, a slight increase from the 38 crashes reported in November 2023. This represents a 2.6% rise in total crashes year-over-year. A notable shift includes the emergence of 2 hit-and-run crashes in the current period, compared to none in the prior year.

39

2.6%was 38

Total Crash Events

0

Persons Killed

14

27.3%was 11

Persons Injured

2

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in Ludlow showed a slight upward trend, with total crashes increasing by 2.6% from 38 to 39. Total injuries also rose by 27.3%, from 11 in November 2023 to 14 in November 2024. Fatalities remained at zero for both periods.

2

Hit-and-Run Crashes — November 2024

5.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Pedestrians Injured

Prior: 0%

12

Motorists Injured

Prior: 1020.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 between the two periods. In November 2024, the peak day for crashes was Friday with 10 incidents, and the peak hour was 8 PM with 5 crashes. This contrasts with November 2023, where Wednesday saw the most crashes with 12 incidents, and the peak hour was 3 PM with 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity distributions saw notable changes, though no fatalities occurred in either period. Minor injuries increased significantly, with 12 crashes (30.8% of total) in November 2024 compared to 5 crashes (13.2% of total) in November 2023. Additionally, 5 crashes with possible injuries were reported in the prior period, while none were recorded in the current period.

Outcome by Severity (Crash Events)

Minor Injury12minor injury crashes30.8%
140.0%prior 5
No Injury27no injury crashes69.2%
-3.6%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record

Top Contributing Factors

Key contributing factors showed shifts in their counts year-over-year. 'Inattention' decreased from 11 crashes in November 2023 to 7 crashes in November 2024, a reduction of 4 crashes. Conversely, 'Failed to yield right of way' increased from 2 crashes to 7 crashes, a rise of 5 crashes. 'No improper driving' also saw a decrease from 9 crashes to 6 crashes.

Officer-Reported Primary Contributing Cause

Inattention7 (17.9%)-36.4%prior 11
Failed to yield right of way7 (17.9%)
No improper driving6 (15.4%)-33.3%prior 9
Failure to keep in proper lane or running off road4 (10.3%)
Distracted2 (5.1%)
Fatigued/asleep2 (5.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5.1%)
Followed too closely1 (2.6%)
Operating defective equipment1 (2.6%)
Driving too fast for conditions1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Regarding crash conditions, the number of crashes occurring in 'Daylight' decreased from 22 in November 2023 to 15 in November 2024. Conversely, crashes in 'Dark - lighted roadway' conditions increased from 5 to 13 incidents. Crashes on 'Wet' road surfaces rose from 4 to 7 year-over-year, while those on 'Dry' surfaces slightly decreased from 34 to 32.

Weather

Clear23 (59.0%)
-14.8%prior 27
Clear/Clear6 (15.4%)
Rain2 (5.1%)
Clear/Other2 (5.1%)
Rain/Clear1 (2.6%)
Rain/Cloudy1 (2.6%)
Rain/Rain1 (2.6%)
Clear/Cloudy1 (2.6%)
Cloudy1 (2.6%)
Cloudy/Rain1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash

Lighting

Daylight15 (38.5%)
-31.8%prior 22
Dark - lighted roadway13 (33.3%)
160.0%prior 5
Dusk7 (17.9%)
0.0%prior 7
Dark - roadway not lighted3 (7.7%)
Dawn1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field

Road Surface

Dry32 (82.1%)
-5.9%prior 34
Wet7 (17.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field

Vehicles & Demographics

The composition of vehicles involved and persons affected saw changes. The total number of persons involved in crashes increased from 69 to 97. Among vehicle makes, Honda's involvement decreased from 11 vehicles to 5, while Hyundai's involvement increased from 2 to 9 vehicles. Toyota remained a top make, with 9 vehicles in the prior period and 10 in the current period.

Top Vehicle Makes (70 vehicles)

1
TOYOTA10 (14.3%)
11.1%prior 9
2
HYUNDAI9 (12.9%)
3
FORD7 (10%)
40.0%prior 5
4
NISSAN6 (8.6%)
-25.0%prior 8
5
HONDA5 (7.1%)
-54.5%prior 11
6
RAM3 (4.3%)
7
CHEVROLET3 (4.3%)
-57.1%prior 7
8
LEXUS2 (2.9%)
9
MAZDA2 (2.9%)
10
VOLKSWAGEN2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records

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

Sex Distribution (89 persons with recorded sex)

Male48 (53.9%)
14.3%prior 42
Female41 (46.1%)
78.3%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes at 35 mph speed limits decreased from 15 in November 2023 to 8 in November 2024. Conversely, crashes at 30 mph speed limits increased from 5 to 11, and those at 65 mph speed limits doubled from 5 to 10. No fatalities were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-11-01 through 2024-11-30 (30 days)
  • Geographic scope: LUDLOW, MA
  • Total crash records analyzed: 39
  • Total persons involved: 97
  • Total vehicles involved: 70

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). "LUDLOW, MA Crash Intelligence Report: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ludlow/november-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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Ludlow, MA Crash Report — November 2024 | ThatCarHitMe.com