Monthly Traffic Safety Analysis

30 CRASHES IN
LUDLOW, MA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, Ludlow experienced 30 crashes, a 25% decrease from the 40 crashes recorded in April 2022. Total injuries also saw a substantial reduction, falling by 54.5% from 11 to 5. A notable shift was the occurrence of one hit-and-run crash in the current period, compared to zero in the prior year.

30

▼ -25.0%was 40

Total Crash Events

0

Persons Killed

5

▼ -54.5%was 11

Persons Injured

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend indicates a significant decrease in crash activity in April 2023 compared to the same month in the prior year. Total crashes fell by 25%, from 40 to 30, while total injuries decreased by 54.5%, from 11 to 5.

1

Hit-and-Run Crashes — April 2023

3.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

5

Motorists Injured

Prior: 10↓-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns show a shift in the peak day for crashes, moving from Saturday with 10 crashes in April 2022 to Friday with 7 crashes in April 2023. While 3 p.m. remained the peak hour for both periods, the number of crashes at this hour decreased from 8 to 4. Notably, crashes on Wednesdays increased from 1 to 6, while crashes on Tuesdays decreased from 6 to 0.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either April 2023 or April 2022. Total injuries decreased by 54.5%, from 11 to 5. The prior period included one serious injury crash (2.5% share), which was absent in the current period, while minor injury crashes increased from 3 (7.5% share) to 4 (13.3% share).

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes13.3%
↑33.3%prior 3
Possible Injury1possible injury crashes3.3%
↓-50.0%prior 2
No Injury23no injury crashes76.7%
↓-28.1%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'No improper driving,' decreased from 10 crashes in April 2022 to 8 crashes in April 2023. Conversely, 'Inattention' crashes increased from 4 to 7, becoming a more prominent factor in the current period. Crashes attributed to 'Failed to yield right of way' decreased from 3 to 1, while 'Disregarded traffic signs, signals, road markings' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' both increased from 1 to 2 crashes.

Officer-Reported Primary Contributing Cause

No improper driving8 (26.7%)↓-20.0%prior 10
Inattention7 (23.3%)
Disregarded traffic signs, signals, road markings2 (6.7%)
Failure to keep in proper lane or running off road2 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (6.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (6.7%)
Failed to yield right of way1 (3.3%)
Operating defective equipment1 (3.3%)
Wrong side or wrong way1 (3.3%)
Visibility obstructed1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased slightly from 24 to 25, despite an overall decrease in total crashes. Crashes during 'Rain' conditions decreased from 4 to 1, and those on 'Wet' road surfaces decreased from 6 to 4. Similarly, crashes during 'Daylight' conditions saw a reduction from 31 to 25.

Weather

Clear25 (83.3%)
↑4.2%prior 24
Cloudy/Rain2 (6.7%)
Clear/Rain1 (3.3%)
Cloudy/Clear1 (3.3%)
Rain1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight25 (83.3%)
↓-19.4%prior 31
Dark - lighted roadway2 (6.7%)
Dark - roadway not lighted2 (6.7%)
Dusk1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry26 (86.7%)
↓-23.5%prior 34
Wet4 (13.3%)
↓-33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (49 vehicles)

1
HONDA8 (16.3%)
↓-38.5%prior 13
2
HYUNDAI7 (14.3%)
3
CHEVROLET5 (10.2%)
↓-28.6%prior 7
4
FORD4 (8.2%)
↓-60.0%prior 10
5
BMW2 (4.1%)
6
CHRYSLER2 (4.1%)
7
FREIGHTLINER2 (4.1%)
8
JEEP2 (4.1%)
9
KIA2 (4.1%)
10
NISSAN2 (4.1%)
↓-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

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

Sex Distribution (57 persons with recorded sex)

Female32 (56.1%)
↓-11.1%prior 36
Male25 (43.9%)
↓-53.7%prior 54

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed limit zone for either period. The 35 mph speed zone experienced the largest numerical decrease in crashes, falling from 14 in April 2022 to 9 in April 2023. Crashes in the 25 mph zone decreased from 8 to 7, and in the 30 mph zone from 7 to 6, indicating a general reduction across most speed categories.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: LUDLOW, MA
  • Total crash records analyzed: 30
  • Total persons involved: 60
  • Total vehicles involved: 49

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: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ludlow/april-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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Ludlow, MA Crash Report — April 2023 | ThatCarHitMe.com