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On June 11, 2018, a Cruise autonomous vehicle was rear-ended by another Cruise vehicle being operated in conventional mode by a human employee in San Francisco. The incident resulted in minor property damage to both vehicles, with no injuries reported. The event was documented in a collision report submitted to the California Department of Motor Vehicles.
In San Francisco, an autonomous Cruise Chevrolet Bolt collided with another Cruise vehicle driven by a Cruise human employee, causing minor scuffs to the cars but no human injuries.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.
The incident highlights the challenges of autonomous vehicles operating in complex human environments, where the AI's overly cautious programming can lead to unexpected interactions and collisions with human drivers.
Human
Due to a decision or action made by humans
Unintentional
Due to an unexpected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The collision was caused by a human employee driving a Cruise vehicle in conventional mode who rear-ended an autonomous Cruise vehicle. The human driver did not intend to cause the accident, which occurred during post-deployment testing on public streets.
A minor, non-injury traffic collision involving two GM Cruise test vehicles in San Francisco. The incident represents a routine testing mishap with negligible national security implications.
The report describes a Cruise vehicle operating in autonomous mode on the streets of San Francisco, navigating turns and traffic dynamically. It responds to environmental inputs using learned patterns and makes real-time decisions without explicit human planning.
High Risk: The system is an autonomous vehicle operating in public traffic, which falls under critical infrastructure and safety-critical transport systems. The report describes it operating on public streets where failures can have significant implications for physical safety.
The AI system's primary function is to operate a self-driving vehicle autonomously on public roads.
The reports provide clear, consistent details about the specific collision on June 11, 2018, including the modes of operation of both vehicles, the lack of injuries, and the minor nature of the property damage. The facts are well-documented via official DMV reports.
None
Technology
Overly Cautious Programming
AV programmed to be hyper-cautious, causing unexpected braking for humans.
Strict Traffic Law Adherence
AV stops fully and abruptly, mismatching typical human driving expectations.
Data Inputs
Complex Urban Edge Cases
San Francisco streets present dense, unpredictable data inputs for the AV.
Human Factors
Human Driver Error
The trailing vehicle's human driver failed to react to the AV's stop.
Human-AV Interaction Gap
Humans do not expect vehicles to follow traffic laws to a strict T.
Process and Methods
Mixed-Mode Testing
Testing autonomous and human-driven vehicles in close proximity.
Management
Safety Over Smoothness Policy
Management prioritized conservative safety behaviors over natural driving flow.
Regulatory Environment
Self-Reporting Regulations
Allows companies to self-report minor incidents without active oversight.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
