Two Waymo Robotaxis Allegedly Contributed to Bike-Lane Collision That Injured San Francisco Cyclist

A cyclist in San Francisco was injured after a Waymo robotaxi stopped in a bike lane and a passenger opened a door into her path, causing her to collide with the vehicle and a second Waymo. The victim alleges that Waymo's 'Safe Exit' system failed to warn the passenger of the approaching cyclist. The incident resulted in serious bodily injuries and a lawsuit against Waymo and Alphabet.

San Francisco cyclist Jenifer Hanki alleged that on February 16, 2025, one driverless Waymo stopped beside a marked bike lane at a no-stopping curb without warning a passenger who opened a rear door into her path, while a second Waymo crossed into the lane and restricted her escape. Hanki said she suffered brain, spinal, and soft-tissue injuries after striking the door and second vehicle. Her lawsuit alleged failures in Waymo's Safe Exit system and passenger drop-off controls.

Source: AI Incident Database

Risk classification

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

The incident was primarily caused by a technical failure of the Waymo Safe Exit system to perform its designed function of detecting and warning about an approaching cyclist.

Causal factors

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

The collision was caused by the Waymo AI system pulling into a bike lane and its Safe Exit system failing to warn passengers of an oncoming cyclist during active deployment.

EU AI Act risk tier

  • Risk tier: 2 High Risk

High Risk: The AI system is used in critical transport infrastructure (autonomous road vehicles), which has significant implications for public safety and physical well-being.

AI system and alleged parties

  • AI system: Waymo Safe Exit (Waymo)
  • AI purpose: Autonomous Driving
  • Behaviour type: Autonomous
  • Alleged developer: Waymo, Automated driving system developers
  • Alleged deployer: Waymo, Robotaxi operators, Automated driving system deployers
  • Alleged harmed parties: Road users, Jenifer Hanki, Bicyclists

Harm severity

Highest direct severity in any category: Minor. 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 Minor, indirect Negligible
  • Infrastructure: direct Negligible, indirect Negligible
  • Property: direct Negligible, indirect Negligible
  • Financial: direct Minor, indirect Minor
  • 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 Minor, indirect Negligible
  • Epistemic: direct Negligible, indirect Negligible
  • Child sexual exploitation and abuse: direct Negligible, indirect Negligible

Physical

Reported: The report explicitly describes serious physical injuries to the cyclist caused by the collision.

Directly caused: Hanki suffered a brain injury, spine damage, and soft tissue damage after colliding with the Waymo door and being thrown into a second vehicle.

Indirectly caused: N/A

Inferred additional harm: N/A

Financial

Reported: The report describes financial impacts including lost work and an active lawsuit seeking unspecified damages.

Directly caused: The victim suffered loss of income due to being kept out of work by her injuries.

Indirectly caused: The victim incurred medical expenses from ambulance transport and hospitalization, as well as legal costs from filing a lawsuit.

Inferred additional harm: N/A

Psychological

Reported: The report explicitly describes psychological distress and anxiety experienced by the victim.

Directly caused: Hanki reported suffering from emotional distress, anxiety, stress, and a persistent fear of cycling that has kept her off bicycles.

Indirectly caused: N/A

Inferred additional harm: N/A

People affected

  • Occurrences reported: 1
  • People reportedly harmed: 1
  • People reportedly exposed: 5

Potential causes

Management

  • Premature Deployment: Deploying autonomous vehicles before fully refining safe exit technology.

Technology

  • Safe Exit System Failure: The system failed to detect the cyclist and warn the passengers.
  • Improper Stopping Location: The vehicle pulled into a marked bike lane next to a no-stopping sign.
  • Second Vehicle Pathing: A second Waymo pulled into the bike lane, compounding the collision.

Human Factors

  • Passenger Opened Door Prematurely: The passenger popped open the back door into the active bike lane.
  • Lack of Driver Supervision: No human driver was present to monitor traffic or lock doors.
  • Passenger Confusion Post-Incident: Passengers did not know how to report the incident and left the scene.

Process and Methods

  • Inadequate Emergency Reporting: No clear process was provided for passengers to report the collision.
  • Post-Crash Obstruction: Vehicles remained stationary, obstructing traffic and the bike lane.
  • Inadequate Testing and Refining: The technology was deployed without sufficient testing for dooring risks.

Regulatory Environment

  • Gap in Accountability: Lack of clear regulatory standards and accountability for AV companies.

Information quality

  • Classification confidence: High
  • Reason for confidence: The report provides a clear, detailed account of a specific physical collision, the parties involved, the injuries sustained, and the legal action taken, leaving little ambiguity about the core events.
  • Ambiguities identified: The exact technical reason for the Safe Exit system's failure to detect the cyclist is not specified.
  • Alternative interpretations: None, as the physical collision and system failure are clearly documented in the legal filings and news report.

A localized commercial robotaxi accident in San Francisco resulted in physical injury to a cyclist after a passenger opened a door. While highlighting public safety risks of autonomous vehicle deployment, the incident has negligible national security implications and is manageable under standard local legal and regulatory frameworks.

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

Threat characteristics

  • Imminence: Long-term. Represents an ongoing regulatory and safety monitoring concern rather than an active national security crisis.
  • Autonomy: Full autonomy. The Waymo robotaxi operates autonomously on public streets, making real-time driving decisions without a human driver.
  • Novelty: Established threat. Autonomous vehicle traffic incidents and passenger-related collisions on public roads are known, recurring events.

Impact by dimension

  • Physical security: Minor. Localized physical injury to a cyclist due to commercial autonomous vehicle system failure, manageable under standard local traffic safety and civil legal procedures.
  • Information security: Negligible. No information warfare, intelligence compromise, or systematic information manipulation occurred in this incident.
  • Sovereignty: Negligible. No threat to state authority, electoral processes, or core government functions.
  • Economic security: Negligible. No threat to strategic industries, financial markets, or national technological competitiveness.
  • Societal stability: Negligible. No threat to social cohesion, civil liberties, or population-scale stability.
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