Drawn from published evidence and regulatory guidance specific to transport and logistics. Each is pre-scored on a 5×5 likelihood × impact matrix in the Risk Register tool and referenced in the generated policy.
CriticalLikelihood 3 · Impact 5
AI Autonomous Vehicle or ADAS Failure Causing Fatal Road Traffic Accident
An AI autonomous driving system or advanced driver assistance system exhibits unexpected behaviour — through failure to recognise an unusual road scenario, sensor degradation in adverse weather, edge case encounter outside the operational design domain, or model drift after an over-the-air update — causing loss of vehicle control, collision with pedestrians, cyclists, or other vehicles, or failure of emergency braking that results in fatal or serious injury accidents that the AI was specifically designed and marketed to prevent.
CriticalLikelihood 2 · Impact 5
AI Air Traffic Management System Failure or Cyberattack Creating Mid-Air Collision Risk
An AI-assisted or AI-augmented air traffic management system produces conflicting clearances, fails to detect imminent loss of separation, exhibits unexpected automation behaviour during high-density traffic or emergency scenarios, or is compromised through cyberattack in a manner that impairs separation assurance and creates conditions for mid-air collision, controlled flight into terrain, or runway incursion — constituting a catastrophic safety risk to aviation.
CriticalLikelihood 4 · Impact 5
AI Route Optimisation and Scheduling Pressure Driving Driver Hours Violations and Fatigue Accidents
AI fleet management, route planning, and load scheduling systems optimise delivery windows and driver utilisation in ways that create implicit or explicit pressure on commercial vehicle drivers to violate mandatory driving time limits and rest period requirements — through delivery commitments that cannot be met within legal hours, AI performance scoring that penalises compliant rest periods, or AI routing that assumes non-compliant journey times — contributing to driver fatigue accidents on public roads with serious injury consequences.
CriticalLikelihood 3 · Impact 5
Cyberattack on AI-Controlled Transport Infrastructure Causing Coordinated Disruption
State or sophisticated criminal threat actors compromise AI traffic management systems, AI rail signalling platforms, AI port management systems, or AI logistics coordination networks — through adversarial manipulation of sensor inputs, ransomware targeting AI operational platforms, or supply chain compromise of AI transport software — causing coordinated disruption to transport infrastructure affecting millions of passengers and freight movements, generating cascading economic harm, and potentially creating conditions for physical accidents.
HighLikelihood 4 · Impact 4
AI Gig Worker Scheduling and Algorithmic Management Causing Labour Harm and Regulatory Violations
AI algorithmic management systems used by ride-hailing, parcel delivery, and courier platforms to assign work, set pay rates, evaluate performance, and make deactivation decisions create serious worker harm — including AI-generated work allocation that constitutes employment in substance without employment protections, AI performance scoring that does not account for legitimate service disruptions, AI pay-setting that fails to guarantee minimum wage, and opaque AI deactivation that denies workers access to their livelihood without explanation or appeals process.
CriticalLikelihood 3 · Impact 5
AI Predictive Maintenance Failure on Safety-Critical Transport Assets
AI predictive maintenance systems for aircraft, rail rolling stock, commercial vehicles, or maritime vessels produce incorrect remaining useful life predictions — through model drift as assets age beyond training distribution, failure mode novelty, or sensor data quality degradation — resulting in either unscheduled asset failure during operation creating safety incidents, or systematic maintenance deferral across a fleet that increases statistical probability of in-service failure affecting passenger safety.