SOTIF

Abstract: Yoav Hollander is a world-class expert in chip verification. The company he founded, Foretellix, brought coverage-driven verification (CDV) into autonomous driving. Recently he wrote a post pushing the methodology into a much larger arena: AI alignment. This post reads that cross-domain migration from my own research field — the SOTIF four-quadrant model, the tree-like structure of Robot SOTIF, and the standards-driven Chinese context. The core question stays the same throughout: how do you know what you don’t know? ...

Abstract: ASIL E is not a published standard. Its real value is not the name of a higher integrity level, but the question it forces Level 4 and Level 5 autonomous-driving safety arguments to answer: when there is no human fallback, can the safety case still credit a human controller? For me, the useful translation is not “ASIL E compliance.” It is a no-human-fallback review lens, four evidence fields in ADSafetyPilot, and a feedback loop connecting ROAM, DRIVEResearch, and a field-monitoring-backed safety case. ...

Abstract: On June 2, 2026, the Chinese national standard project 机器人预期功能安全实施指南 entered public notice, with the comment period scheduled to close on July 2, 2026. I have put this direction into OpenTopic as the second open research theme: Robot SOTIF. The goal is not to copy autonomous-driving SOTIF directly into robotics, but to build an evidence chain from standards, ODD, scenarios, triggering conditions, physical interaction, LLM/VLA decision safety, and finally to a defensible safety case. ...

Abstract: When the AI in a driverless car can’t handle the situation, does the industry have a coherent emergency-management playbook? It doesn’t — and worse, no reference standard exists. Starting from the March 31, 2026 Wuhan Apollo Go incident, this post walks through three recent body blows to the Robotaxi industry, scans every gap in the ISO / SAE / IEC / China standards landscape on remote operations, traces the fundamental regulatory pivot after Wuhan, and introduces ROAM (Remote Operations & Anomaly Management) — an open-source reference architecture with four modules, ten future operating models, and a 52-standard scan that confirms the void. ...

Abstract: In Q1 2026, “Harness Engineering” surfaced almost simultaneously at OpenAI, Anthropic, and the Chinese startup Nextie, and the “12 Primitives” converged in the open-source community as a shared taxonomy. This essay argues that essentially all mainstream investment in Harness has concentrated in a single dimension — user experience, performance, efficiency — while the dimension that actually determines market access in Safety-Critical domains (autonomous driving, medical AI, financial risk control) has been collectively skipped: safety compliance. By constructing a two-way mapping between the 12 Harness Primitives and SOTIF (ISO 21448), this essay identifies 12 concrete research directions, offered as a starting point for standardization bodies, corporate R&D, third-party institutions, and academic labs to jointly fill in this commons. A ~3000-word Chinese short form is available on the author’s WeChat channel. ...

Abstract: In early 2026, Harness Engineering rose quickly in the AI engineering community, becoming a third-generation methodology after Prompt Engineering and Context Engineering. Starting from the core concept of Harness Engineering, this article systematically analyzes its deep correspondence with today’s end-to-end intelligent-driving systems across the full lifecycle. It argues that the two fields are structurally isomorphic in their control-theoretic framework, improvement loops, and philosophy of failure response. It also discusses the reference value of Harness Engineering for intelligent-driving user experience and safety engineering, especially SOTIF / ISO 21448. The central finding is that Harness Engineering and automotive safety engineering are not superficially similar metaphors. They are two independently evolved solutions to the same class of root problems, sharing the same underlying operating system. ...

Abstract: Bosch Lead Engineer Thejeswarareddy R open-sourced an agent system that systematically injects automotive engineering standards into Claude Code, covering 75+ skill categories. I forked it and added autonomous driving safety standards (ISO 21448/34502/4804, etc.), upcoming mandatory Chinese national standards, and in-depth SOTIF engineering practices. This article breaks down the project’s architectural highlights and my additions. Figure 1 If you are a junior functional safety engineer in the automotive industry, you have almost certainly lived through this scenario: ...

Abstract: End-to-end architectures are moving from research papers to mass production, yet the cornerstone of global autonomous driving safety evaluation — scenario-based development and testing — still rests on the assumption that systems can be decomposed into perception, planning, and control modules. This article systematically analyzes five structural challenges that scenario methods face in the end-to-end era, argues that they remain valid but are no longer sufficient, and proposes an evolutionary path that supplements scenario methods with large-scale aerial naturalistic driving data within a three-layer collaborative framework. ...

Abstract: In March 2026, JAMA released the fourth edition (Ver.4.0) of the SAKURA Automated Driving Safety Evaluation Framework — a 344-page national-level safety evaluation technical document. This article systematically examines this safety evaluation system jointly developed by Toyota, Honda, Nissan, and other major Japanese automakers, covering its corporate value, engineering perspectives, core methodology, and the frontier challenges posed by the end-to-end AI era, while exploring its implications for China’s standardization efforts. ...

Abstract: In March 2026, Germany’s VDA published the global automotive industry’s first standardized guideline for AI quality management — VDA 20 AI in Quality Management (191 pages). This article provides an in-depth analysis of its AIQM three-tier risk classification, 80-item checklist, and 12 application cases. It examines the reference value for China’s autonomous driving industry and explores China’s leading advantages and window of opportunity in end-to-end evaluation methodologies and data infrastructure. ...