Source record

FRA, “TGMS Inspections,” NPRM, October 24, 2024 (one-hour timeframe compared against industry practice ranging from immediate action on crewed vehicles to 24 hours or more on uncre

Method: Literature

FRA, “TGMS Inspections,” NPRM, October 24, 2024 (one-hour timeframe compared against industry practice ranging from immediate action on crewed vehicles to 24 hours or more on uncrewed systems).

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI

A Framework for Trustworthy Deployment: Governance, Human-Automation Teaming, and a Phased Implementation Roadmap for AI in Track Base Management

When the Model Is Wrong: Risks, Hazards, and Failure Modes of AI in Safety-Critical Track Inspection

The Economics of Knowing: Predictive Maintenance, Degradation Forecasting, and the Asset Value Case for Substructure AI