Examining Key Incidents in Autonomous Robotaxis: Waymo, Pony.AI, Olli and Their Implications

Recent accidents involving autonomous robotaxis from companies like Waymo, Pony.AI, and Olli have raised concerns about the safety and reliability of self-driving vehicles. These incidents serve as valuable learning opportunities for the development of responsible AI in transportation. Understanding the root causes, identifying gaps in AI governance, and implementing safeguards are crucial to build trustworthy AI models. The HISPI Project Cerebellum TAIM provides a platform for mapping, measuring, and managing such incidents. Through JOIN US, contribute to our community and help shape the future of safe and secure AI.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MEASURE 2.6 — similarity 0.635, rank 1. TAIM detail and related incidents →
MANAGE 4.3 — similarity 0.623, rank 2. TAIM detail and related incidents →
MAP 4.2 — similarity 0.619, rank 3. TAIM detail and related incidents →

Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/151

Data source

Incident data is from the AI Incident Database (AIID).

When citing the database as a whole, please use:

McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.

Pre-print on arXiv · Database snapshots & citation guide

We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.