ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LUDLOW, MA · MAY 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/ludlow/may-2023-report
Monthly Traffic Safety Analysis
46 CRASHES IN
LUDLOW, MA
MAY 2023
In May 2023, Ludlow experienced 46 total crashes, a slight increase from the 45 crashes recorded in May 2022, representing a 2.2% rise. A notable shift was the absence of fatalities in May 2023, compared to one fatality in May 2022. However, total injuries increased significantly from 8 to 16.
46
▲ 2.2%was 45
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
16
▲ 100.0%was 8
Persons Injured
7
▲ 75.0%was 4
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for total crashes in Ludlow remained relatively stable year-over-year, with a minor increase of 1 crash from 45 to 46. However, total injuries saw a substantial increase of 100%, rising from 8 in May 2022 to 16 in May 2023. Conversely, fatalities decreased from 1 in May 2022 to 0 in May 2023.
7
Hit-and-Run Crashes — May 2023
▲ 75.0% vs prior (4)
Hit-and-run crashes increased from 4 in May 2022 to 7 in May 2023, a 75% increase in count. This resulted in the hit-and-run rate rising from 8.9% of all crashes in May 2022 to 15.2% in May 2023. This indicates an upward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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 Tuesday with 11 crashes in May 2022 to Wednesday with 9 crashes in May 2023. The peak hour for crashes also changed, moving from 6 PM with 5 crashes in May 2022 to 5 PM with 9 crashes in May 2023. Crashes on Mondays and Tuesdays decreased by 6 and 5 respectively, while Fridays and Saturdays saw increases of 4 and 3 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased from 1 in May 2022 to 0 in May 2023, resulting in a fatal rate of 0% for the current period compared to 2.2% previously. Minor injury crashes increased from 5 to 7, and possible injury crashes rose from 2 to 5 year-over-year. Crashes with no injury decreased from 33 to 30.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the leading contributing factor, increasing from 10 crashes in May 2022 to 14 crashes in May 2023, a 40% increase in count. Crashes attributed to 'No improper driving' also increased by 3, from 8 to 11. Conversely, 'Failed to yield right of way' decreased by 2 crashes, from 5 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in 'Clear' weather conditions slightly increased from 31 in May 2022 to 33 in May 2023. Crashes in 'Cloudy' conditions decreased from 5 to 3 year-over-year. The number of crashes occurring during 'Daylight' hours increased from 34 to 37, while those in 'Dark - lighted roadway' conditions decreased from 9 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 74 in May 2022 to 84 in May 2023. Toyota vehicles involved in crashes increased by 6, from 8 to 14, becoming the most frequent make. Honda maintained its count of 11 vehicles, while Hyundai saw an increase from 2 to 5 vehicles involved.
Top Vehicle Makes (84 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records
17 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (91 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 65 mph speed zone saw the most significant increase, rising from 1 in May 2022 to 5 in May 2023. The 5 mph speed zone appeared in May 2023 with 3 crashes, whereas it was not present in May 2022 data. The prior period recorded 1 fatality in the 30 mph zone, while no fatalities were recorded across any speed zones in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-05-01 through 2023-05-31 (31 days)
- Geographic scope: LUDLOW, MA
- Total crash records analyzed: 46
- Total persons involved: 109
- Total vehicles involved: 84
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 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ludlow/may-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-05-01 – 2023-05-31
Generated: June 21, 2026 · All rights reserved