ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LUDLOW, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
527 CRASHES IN
LUDLOW, MA
2023
In 2023, Ludlow recorded 527 total traffic crashes, a 4.7% decrease from the 553 crashes reported in 2022. While overall crashes declined, the number of fatalities doubled from one in the prior year to two in the current year. The most significant shift in contributing factors was a 25.4% increase in crashes attributed to inattention, which rose from 126 incidents in 2022 to 158 in 2023.
527
▼ -4.7%was 553
Total Crash Events
2
▲ 100.0%was 1
Persons Killed
139
▲ 1.5%was 137
Persons Injured
33
▼ -8.3%was 36
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 22 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic crashes in Ludlow showed a slight downward trend, decreasing by 4.7% from 553 in 2022 to 527 in 2023. Despite this decrease in total incidents, the human cost of crashes increased, with total injuries rising slightly from 137 to 139 and fatalities doubling from one to two year-over-year.
33
Hit-and-Run Crashes — 2023
▼ -8.3% vs prior (36)
Hit-and-run incidents saw a minor decrease between the two periods. The total count of hit-and-run crashes fell from 36 in 2022 to 33 in 2023. The hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, also trended down slightly, from 6.5% in the prior year to 6.3% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
5
Pedestrians Injured
2
Cyclists Injured
132
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a notable shift in the peak day of the week, moving from Tuesday (97 crashes) in 2022 to Friday (99 crashes) in 2023. However, the peak hour for collisions remained consistent, with the 3 p.m. hour being the most frequent time for crashes in both periods, accounting for 57 incidents in 2022 and 52 in 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted year-over-year. While total crashes decreased, fatal crashes doubled from one to two, increasing the fatal crash share from 0.2% to 0.4%. Crashes resulting in serious injuries saw a significant drop, falling from 11 in 2022 to 5 in 2023. Conversely, minor injury crashes increased from 62 to 72, and their share of all crashes rose from 11.2% to 13.7%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
Inattention was the leading contributing factor in both years, and its prevalence grew significantly; the count of inattention-related crashes increased by 25.4%, from 126 in 2022 to 158 in 2023. Consequently, its share of all crashes rose from 22.8% to 30.0%. In contrast, crashes attributed to following too closely decreased by more than half, from 32 incidents in 2022 to 14 in 2023. Failing to yield the right of way also saw a decrease in count, from 38 to 29 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained largely stable between the two periods, with the majority of incidents in both years occurring in daylight, on dry roads, and in clear weather. In 2023, 68.5% of crashes happened in daylight, compared to 67.8% in 2022. Similarly, dry road conditions were present in 79.0% of crashes in 2023, nearly identical to the 79.2% reported in 2022. Crashes on wet roads saw a slight increase from 79 to 85 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent year-over-year: Honda, Toyota, and Ford led the rankings in both 2022 and 2023, though the total count for each make decreased. The age demographics of persons involved in crashes showed a slight shift, with the 26-34 age group's representation increasing from 12.9% of all persons in 2022 to 14.8% in 2023. Other age groups, such as the 16-20 and 65+ cohorts, saw their share of involvement remain relatively stable.
Top Vehicle Makes (916 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
91 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,032 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones was consistent year-over-year, with the 35 mph, 30 mph, and 25 mph zones accounting for the highest number of incidents in both periods. In 2022, the single fatal crash occurred in a 30 mph zone. In 2023, the two fatal crashes occurred in a 30 mph zone and a 40 mph zone, respectively.
Fatal crashes by zone: 30 mph: 1 of 120 (0.833%) · 40 mph: 1 of 32 (3.125%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: LUDLOW, MA
- Total crash records analyzed: 527
- Total persons involved: 1,142
- Total vehicles involved: 916
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/ludlow/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved