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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Software Reliability Growth Models Predict Autonomous Vehicle Disengagement Events · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1812.08901/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1812.08901/feed.xml" rel="self" type="application/rss+xml" /><item><title>Software Reliability Growth Models Predict Autonomous Vehicle Disengagement Events — mentioned by rgmerk</title><link>https://news.ycombinator.com/item?id=30185576</link><guid isPermaLink="false">urn:hackerpapers:mention:1812.08901:30185576</guid><pubDate>Wed, 02 Feb 2022 23:14:12 GMT</pubDate><description>&lt;p&gt;Kalra and Paddock&amp;#x27;s analysis is correct as far as it goes, but it&amp;#x27;s easy to misuse to claim that we couldn&amp;#x27;t feasibly demonstrate an autonomous vehicle is acceptably safe. It never got accepted for publication because the reviewers didn&amp;#x27;t think it was significant enough, but I wrote a paper presenting an alternative way to analyse autonomous vehicle reliability data (you&amp;#x27;ll have to take my word for it, but the reviewers didn&amp;#x27;t quibble about the results presented, just whether it was important): https://arxiv.org/pdf/1812.08901.pdf The major technical contribution was demonstrating that a…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1812.08901/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.SE</category></item></channel></rss>
