Drive S(AI)FE

Smarter Fatigue Management. Safer Roads. Better Decisions.

We're building a human-centred, ethical AI fatigue management system designed for real-world fleet operations — from large logistics providers to smaller operators preparing for the future of AI-enabled safety.
Our platform integrates seamlessly with existing fleet technology to detect fatigue risk early, support drivers proactively, and give fleet managers the insights they need to act before incidents occur.
AI-powered fatigue management dashboard visualization
01

The Challenge

Fatigue remains one of the most significant safety risks in road transport.

Despite advances in vehicle technology, many fatigue solutions:

  • Rely on reactive alerts rather than prevention
  • Are intrusive or poorly trusted by drivers
  • Require management systems smaller operators don't have
  • Fail to translate AI insights into practical operational decisions

This project addresses those gaps by combining behavioural science, ethical AI, and industry co-design.

02

Our Solution

A scalable, ethical AI system for fatigue detection, prevention, and decision support.

The project delivers an integrated fatigue management ecosystem that works at both the driver level and the fleet level.

Core Components

AI-Powered Fatigue Detection & Prevention

An advanced AI system that integrates:

  • Real-time driver behaviour
  • Biometric and physiological indicators
  • Workplace and operational data

This enables early detection of fatigue risk and supports prevention before safety is compromised.

Personalised Driver Interventions

A non-intrusive, human-centred intervention model that:

  • Adapts to individual drivers
  • Delivers proactive, explainable fatigue alerts
  • Supports behavioural change without surveillance-style monitoring

The goal is support — not punishment.

Fatigue Risk Advisor (FRA) – Fleet-Wide Intelligence

The Fatigue Risk Advisor (FRA) provides fleet managers with early-warning insights through AI-driven risk analysis.

It:

  • Aggregates real-time and historical data
  • Identifies fatigue trends and high-risk periods
  • Supports smarter decisions on shift scheduling, route planning, and workload distribution

The system uses a hybrid architecture:

  • Edge computing for real-time alerts
  • Cloud analytics for fleet-wide reporting and trend analysis

This ensures scalability, adaptability, and proactive risk management.

03

Designed for Real Operations

Built for fleets of all sizes — especially smaller operators.

Many smaller fleet operators will soon have access to AI-enabled technology, but not the governance frameworks or management systems to use it safely and effectively.

This project:

  • Designs systems and toolkits specifically for small and medium operators
  • Reduces reliance on complex internal systems
  • Provides practical, fit-for-purpose guidance that works in the real world
04

Ethics, Trust & Human-Centred Design

Safety, privacy, and trust are built in — not bolted on.

Ethical AI principles underpin the entire project, including:

Explainable AI Decision-Making

Clear, transparent reasoning behind every alert and recommendation so drivers and managers understand why actions are suggested.

Data Privacy & Security Safeguards

Robust protection of sensitive personal and operational data with strict access controls and compliance standards.

Clear Boundaries on Monitoring

Defined limits on data collection and use to prevent surveillance overreach and maintain driver dignity.

Active Co-Design Involvement

Direct participation of drivers and managers in system design ensures practical, trusted solutions.

This ensures the technology supports people — not replaces judgment or autonomy.

05

Industry Collaboration

Co-designed with industry, researchers, and regulators.

The project brings together:

  • Fleet operators and drivers
  • AI, behavioural science, and fatigue experts
  • Universities and research partners
  • Technology providers and regulators

Key insights, risk factors, and framework recommendations will be shared across the industry to support broader adoption of best-practice fatigue management.

06

Project Roadmap

From research to real-world deployment.

Phase 1: Planning & Governance

  • Establish project working group and partnerships
  • Define governance, ethics, and evaluation frameworks
  • Develop stakeholder engagement and communications plans

Phase 2: Research & Data Collection

  • Review AI, behavioural science, and fatigue research
  • Engage industry to understand real challenges and opportunities
  • Collect driver behaviour and workplace fatigue data
  • Produce an industry risk and needs report

Phase 3–4: AI System Design & Development

  • Design AI architecture and data pipelines
  • Train fatigue detection and prediction models
  • Develop personalised driver interventions
  • Integrate the Fatigue Risk Advisor (FRA)

Phase 5: Co-Design & Validation

  • Co-design dashboards with drivers and fleet managers
  • Test usability, clarity, and trust
  • Embed ethics, privacy, and safety controls

Phase 6–7: Real-World Testing

  • Deploy the system in partner fleet trials
  • Refine AI interventions based on feedback
  • Measure fatigue risk reduction at driver and fleet levels

Phase 8: Training & Toolkits

  • Develop driver and manager training modules
  • Create practical AI & fatigue implementation toolkits
  • Tailor resources for small fleet operators
  • Pilot and refine toolkits with industry

Phase 9: Evaluation & Industry Sharing

  • Final project evaluation
  • Industry dissemination of findings
  • Submission of final report to NHVR
07

Outcomes & Impact

What success looks like.

Reduced Fatigue Risk

Measurable reduction in fatigue risk across individual drivers and fleets through proactive detection and intervention.

Better Operational Decisions

Enhanced decision-making capabilities through AI-driven insights on scheduling, routing, and workload management.

Ethical AI Adoption

Practical, ethical AI adoption framework across the transport sector that prioritizes human wellbeing.

Industry-Wide Access

Comprehensive tools, frameworks, and learnings made available to the entire industry, especially smaller operators.

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Get Involved. Stay Informed. Help Shape the Future.

We're actively seeking partners, participants, and collaborators who want to be part of building the next generation of ethical, human-centred fatigue management systems.

Partner with the Project

Join as a research or industry partner to help shape system development.

Participate in Trials

Be part of co-design sessions or real-world testing with your fleet.

Access Future Toolkits

Register your interest to receive implementation guides and resources.

Help us build smarter fatigue management that keeps drivers safe and supports better decisions.

Get in touch