Waymo Robotaxi Reportedly Transported Undetected Person Trapped in Trunk in Los Angeles

In Los Angeles, a Waymo autonomous taxi reportedly picked up a new rider while a man was trapped inside its trunk after a previous passenger left it open. The vehicle's AI systems reportedly did not detect the unauthorized occupant before dispatch. The rider reportedly discovered the man during the trip, and police were called to remove him.

Risk classification

• Primary risk domain: 7 AI system safety, failures, & limitations
• Primary risk subdomain: 7.3 Lack of capability or robustness

The autonomous vehicle's sensors and safety systems failed to detect a human occupant in the trunk before dispatching, demonstrating a lack of capability and robustness in handling edge-case scenarios.

Causal factors

• Entity: AI
• Intent: Unintentional
• Timing: Post-deployment

The incident was caused by the Waymo AI system failing to detect a person in its trunk and dispatching itself, which was an unintentional failure during post-deployment operations.

EU AI Act risk tier

• Risk tier: 2 High Risk

High Risk: The system is an autonomous vehicle used in road traffic and transport infrastructure, which has significant safety implications for passengers and the public.

AI system and alleged parties

• AI system: Waymo autonomous taxi (Waymo)
• AI purpose: Autonomous Driving; Automatic Fault Handling
• Behaviour type: Autonomous
• Alleged developer: Waymo
• Alleged deployer: Waymo
• Alleged harmed parties: Waymo passengers, Unnamed Waymo passenger trapped in trunk

Harm severity

Severity ratings are based on this scale.

Highest direct severity in any category: Negligible. Severity is scored from Negligible to Catastrophic in each harm category, for harm the reports describe as caused directly or indirectly by the AI system.

• Physical: direct Negligible, indirect Negligible
• Infrastructure: direct Negligible, indirect Negligible
• Property: direct Negligible, indirect Negligible
• Financial: direct Negligible, indirect Negligible
• Environmental: direct Negligible, indirect Negligible
• Malicious content: direct Negligible, indirect Negligible
• Differential treatment: direct Negligible, indirect Negligible
• Civil rights: direct Negligible, indirect Negligible
• Democracy: direct Negligible, indirect Negligible
• Privacy: direct Negligible, indirect Negligible
• Psychological: direct Negligible, indirect Negligible
• Epistemic: direct Negligible, indirect Negligible
• Child sexual exploitation and abuse: direct Negligible, indirect Negligible

People affected

• Occurrences reported: 1
• People reportedly harmed: 2
• People reportedly exposed: 3

Potential causes

Management

• Deficient Risk Assessment: Management failed to anticipate unauthorized passenger entry into open trunks.

Technology

• Inadequate Trunk Sensors: Vehicle sensors failed to detect a human occupant inside the closed trunk.
• Lack of Auto-Close Trunk: Vehicle cannot automatically close or lock trunk after passenger exit.

Data Inputs

• Missing Trunk Status Data: System lacked real-time internal trunk occupancy data during dispatch.

Human Factors

• Passenger Negligence: Previous passenger left the vehicle trunk open after completing their ride.
• Unauthorized Trunk Entry: A pedestrian voluntarily climbed into the open trunk of the driverless car.

Process and Methods

• Flawed Dispatch Protocol: System allowed dispatch of vehicle while trunk status was anomalous or open.
• Inadequate Pre-Ride Verification: No physical check of vehicle interior or trunk before starting next trip.

Information quality

• Classification confidence: High
• Reason for confidence: The incident is well-documented with clear timelines, passenger accounts, and company confirmation. The failure mode of the AI system is clear, even if specific technical sensor data is omitted.
• Ambiguities identified: It is not specified whether the vehicle's internal sensors detected the occupant but failed to trigger an alert, or if the trunk area is entirely unmonitored by the system.

A Waymo autonomous vehicle failed to detect an unauthorized passenger trapped in its trunk before dispatching itself to a new customer. While this highlights robustness and safety challenges in autonomous transport systems, it remains a localized, non-adversarial event with minor national security implications.

• Overall national security impact: Minor
• Scope: Single nation
• Primary target: United States
• Alleged perpetrator: Unknown

Threat characteristics

• Imminence: Long-term. The immediate incident is resolved. It represents a long-term strategic safety concern regarding autonomous system edge-cases rather than an active crisis.
• Autonomy: Full autonomy. The autonomous vehicle made dispatching and driving decisions independently without real-time human oversight or intervention.
• Novelty: Evolved capability. While sensor failures in autonomous vehicles are established, the specific failure mode of failing to detect a human trapped in a trunk represents an evolved edge-case scenario.

Impact by dimension

• Physical security: Minor. The incident involves a localized safety failure in an autonomous vehicle system that allowed an unauthorized person to remain trapped in the trunk. While it involves physical transit systems, it was easily managed by local law enforcement and does not threaten critical infrastructure.
• Information security: Negligible. There is no indication of intelligence compromise, cyberattacks, or information warfare operations associated with this incident.
• Sovereignty: Negligible. Core government functions, state authority, and constitutional processes were entirely unaffected by this localized commercial vehicle failure.
• Economic security: Negligible. The incident represents a minor commercial safety issue for a single company and does not threaten strategic industries or national economic security.
• Societal stability: Negligible. The event caused localized distress to the individuals directly involved but does not pose any systemic threat to societal stability or civil liberties.