Google and Delphi Self-Driving Prototypes Allegedly Involved in Near-Miss on San Antonio Road, Palo Alto

A Delphi self-driving Audi Q5 prototype reportedly aborted a lane change after a Google self-driving Lexus RX400h allegedly cut in front of it on San Antonio Road in Palo Alto, California. According to Delphi executive John Absmeier, the Delphi car "took appropriate action" to avoid collision. No crash or injuries occurred.

Risk classification

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

The incident involved a potential driving failure where one autonomous vehicle cut off another, highlighting limitations in real-world driving capability and robustness.

Additional risk subdomains

• 7.6 Multi-agent risks: The incident represents a direct interaction between two independent AI driving agents on a public road, illustrating multi-agent coordination challenges.

Causal factors

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

The incident was caused by the real-time driving decisions of the Google and Delphi autonomous vehicle systems operating on public roads.

EU AI Act risk tier

• Risk tier: 2 High Risk

High Risk: The AI systems are used in critical infrastructure and transport (autonomous driving on public roads), which has significant implications for public safety.

AI system and alleged parties

• AI system: Delphi self-driving Audi Q5, Google self-driving Lexus RX400h (Delphi Automotive, Google)
• AI purpose: Autonomous Driving; Navigation Assistant
• Behaviour type: Autonomous
• Alleged developer: Google, Delphi Technologies
• Alleged deployer: Google, Delphi Technologies
• Alleged harmed parties: John Absmeier, Delphi Technologies

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 exposed: 1

Potential causes

Management

• Prioritizing PR Over Transparency: Companies minimized the incident to protect public perception of AV safety.

Technology

• Lack of Vehicle Coordination: No direct communication between the different autonomous driving systems.
• Aggressive Lane Merging Software: Google car cut off the Delphi vehicle while it was preparing to change lanes.

Data Inputs

• Real-time Sensor Reliance: Vehicles relied purely on local sensors rather than shared intent data.

Human Factors

• Conflicting Executive Accounts: Initial reports of a near-miss were later downplayed by company spokespeople.

Process and Methods

• Lack of Standardized AV Protocols: No shared protocol for how different AVs negotiate lane changes together.
• Public Road Testing Challenges: Testing in real-world traffic introduces unpredictable multi-agent scenarios.

Regulatory Environment

• Confidential Collision Reporting: State laws kept accident reports confidential, limiting public oversight.
• Lack of AV Interaction Rules: No specific regulations governing how different AV brands should interact.

Information quality

• Classification confidence: High
• Reason for confidence: The reports provide consistent details about the core event, including the location, the vehicles involved, and the lack of any physical harm or property damage. Although there is a minor conflict between the initial 'near-miss' characterization and the subsequent corporate downplaying, both accounts agree on the physical facts of the interaction.
• Ambiguities identified: There is some disagreement between the initial Reuters report of a 'near-miss' and the subsequent statements from Google and Delphi claiming the vehicles were never in danger and performed as expected.
• Alternative interpretations: The event could be interpreted either as a minor system failure (cutting off another vehicle) or as a successful demonstration of collision avoidance (the Delphi car successfully aborting the lane change).

A minor, non-collision near-miss between Google and Delphi autonomous prototype vehicles in 2015. The incident represents a standard traffic interaction during early testing of multi-agent autonomous systems, with negligible implications for national security.

• Overall national security impact: Negligible
• Scope: Single nation
• Primary target: No clear primary
• Alleged perpetrator: Unknown

Threat characteristics

• Imminence: Long-term. The incident represents a past, minor testing interaction with no ongoing threat or immediate crisis requiring national response.
• Autonomy: Human-supervised. The vehicles operated autonomously, making real-time driving decisions, though human safety drivers were present to supervise and intervene if necessary.
• Novelty: Evolved capability. An evolved capability representing one of the earliest documented real-world interactions and near-misses between independent multi-agent AI systems on public roads.

Impact by dimension

• Physical security: Negligible. Negligible national security impact. The incident was a minor, non-collision near-miss between two prototype autonomous vehicles on a public road with no injuries, casualties, or infrastructure damage reported.
• Information security: Negligible. No information warfare, intelligence compromise, deepfake operations, or classified data theft occurred during or as a result of this incident.
• Sovereignty: Negligible. No threat to state authority, government decision-making, elections, or constitutional processes. The incident involved private commercial testing.
• Economic security: Negligible. While involving leading autonomous vehicle developers, this minor testing interaction did not involve intellectual property theft, economic warfare, or systemic financial risk.
• Societal stability: Negligible. The incident has no implications for societal stability, civil liberties, mass surveillance, or human rights.