Monthly Traffic Safety Analysis

51 CRASHES IN
LUDLOW, MA
MAY 2024

All metrics benchmarked againstMay 2023

In May 2024, Ludlow experienced 51 total crashes, an increase of 10.9% compared to 46 crashes in May 2023. The most notable year-over-year shift was the increase in total fatalities from 0 in May 2023 to 1 in May 2024. Total injuries decreased by 18.8%, from 16 to 13.

51

10.9%was 46

Total Crash Events

1

Persons Killed

13

-18.8%was 16

Persons Injured

3

-57.1%was 7

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. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in total crashes, rising from 46 in May 2023 to 51 in May 2024, representing a 10.9% increase. Fatalities also increased from 0 to 1, while total injuries decreased by 18.8%.

3

Hit-and-Run Crashes — May 2024

-57.1% vs prior (7)

Hit-and-run crashes decreased from 7 in May 2023 to 3 in May 2024. Consequently, the hit-and-run rate decreased from 15.2% to 5.9% year-over-year, indicating a downward trend.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

13

Motorists Injured

Prior: 15-13.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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 Wednesday (9 crashes) in May 2023 to Thursday (12 crashes) in May 2024. The peak hour also changed, moving from 5 PM (9 crashes) in May 2023 to 1 PM (7 crashes) in May 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes increased from 0 in May 2023 to 1 in May 2024. Minor injury crashes decreased from 7 (15.2% of total crashes) to 5 (9.8% of total crashes) year-over-year. Crashes resulting in no injury increased from 30 (65.2% of total crashes) to 36 (70.6% of total crashes).

Outcome by Severity (Crash Events)

Fatal1fatal crashes2%
Minor Injury5minor injury crashes9.8%
-28.6%prior 7
Possible Injury5possible injury crashes9.8%
0.0%prior 5
No Injury36no injury crashes70.6%
20.0%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Inattention' increased in count from 14 in May 2023 to 19 in May 2024, a 35.7% increase, remaining the top factor. 'No improper driving' decreased from 11 to 7 crashes, a 36.4% decrease in count. 'Failed to yield right of way' doubled in count, rising from 3 to 6 crashes.

Officer-Reported Primary Contributing Cause

Inattention19 (37.3%)35.7%prior 14
No improper driving7 (13.7%)-36.4%prior 11
Failed to yield right of way6 (11.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (5.9%)
Distracted1 (2%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2%)
Other improper action1 (2%)
Over-correcting/over-steering1 (2%)
Visibility obstructed1 (2%)
Made an improper turn1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on wet road surfaces increased from 2 in May 2023 to 7 in May 2024. Crashes during daylight conditions increased from 37 to 42, while those in 'Dark - lighted roadway' conditions decreased from 6 to 5. Clear weather crashes increased from 33 to 38.

Weather

Clear38 (77.6%)
15.2%prior 33
Cloudy/Rain4 (8.2%)
Cloudy/Other2 (4.1%)
Rain2 (4.1%)
Cloudy1 (2.0%)
Clear/Cloudy1 (2.0%)
Rain/Cloudy1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Weather condition at time of crash

Lighting

Daylight42 (85.7%)
13.5%prior 37
Dark - lighted roadway5 (10.2%)
-16.7%prior 6
Dark - roadway not lighted2 (4.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Lighting condition field

Road Surface

Dry42 (84.0%)
0.0%prior 42
Wet7 (14.0%)
Other1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 84 to 99 year-over-year. FORD became the top make involved, increasing from 6 vehicles in May 2023 to 12 in May 2024. TOYOTA vehicles involved decreased from 14 to 11, while HONDA decreased from 11 to 8.

Top Vehicle Makes (99 vehicles)

1
FORD12 (12.1%)
100.0%prior 6
2
TOYOTA11 (11.1%)
-21.4%prior 14
3
CHEVROLET9 (9.1%)
80.0%prior 5
4
HYUNDAI9 (9.1%)
80.0%prior 5
5
HONDA8 (8.1%)
-27.3%prior 11
6
NISSAN7 (7.1%)
-12.5%prior 8
7
GMC5 (5.1%)
8
SUBARU5 (5.1%)
9
ACURA3 (3%)
10
KIA3 (3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Vehicle unit records

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

Sex Distribution (109 persons with recorded sex)

Male63 (57.8%)
21.2%prior 52
Female46 (42.2%)
17.9%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 10 to 13, and crashes in 40 mph zones increased from 1 to 3. Conversely, crashes in 25 mph zones decreased from 12 to 8. A fatal crash occurred in a 40 mph zone in May 2024, whereas no fatal crashes were recorded in any speed zone in May 2023.

Fatal crashes by zone: 40 mph: 1 of 3 (33.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-05-01 to 2024-05-31 · 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: 2024-05-01 through 2024-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-05-01 through 2024-05-31 (31 days)
  • Geographic scope: LUDLOW, MA
  • Total crash records analyzed: 51
  • Total persons involved: 121
  • Total vehicles involved: 99

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: May 2024." Published June 21, 2026. Reporting period: 2024-05-01 to 2024-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ludlow/may-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 — May 2024 | ThatCarHitMe.com