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• W2545341229 abstract "Two recent messages in the press: ‘Tesla Autopilot Crash: Tesla Autopilot Problem To Blame In Fatal Accident In China?’ and ‘Google's self-driving car may have caused first crash’. This editorial will not deal with the technical discussion whether the above statements are right or wrong; that is upon others to decide. The main issue at hand is the impact caused by these articles and their (statistical) justification. It is without any doubt that, if we want to rely our lives (and that of others) to technical systems that these systems must meet with utmost standards of reliability. This requires utmost attention during the design, testing and use phase of these systems. Especially for systems that have to deal with complex situations in real life this includes field-testing. And during these tests, new information will be gathered that is invaluable for the further development of these systems. In spite of several precautions during design, manufacturing and testing, thing can go wrong due to unforeseen circumstances. Fortunately, in most cases, these field accidents are few and far apart. Of course, they should be followed by a thorough analysis and mitigation of the consequences. However, in these particular cases, there was a considerable difference between what happened and how it was brought, via the press, to the general audience. The systems that are under development here are designed in a context where the existing human-operator based systems cause worldwide thousands of fatal accidents every year. Even in a small country like the Netherlands we have an average of about two fatal accidents every day. Therefore, statistically speaking, the newly developed autonomous cars seem to be (although the actual number of data points is still quite small) even with the currently still developing new technology, far safer than the existing human driven cars. Since many of the papers on this issue lack a solid statistical basis and/or context, they easily can result in a very negative attitude of the general audience towards these new systems with, as a consequence, that the introduction of these systems on the market takes far longer than necessary. In the mean time, the existing, known, systems keep, predictably, causing casualties. It is, of course, of imminent importance that new technology is well understood and properly tested before it is put on the market. Solid academic papers based upon high-quality models and/or validated field data in journals like this can certainly contribute to this. Hopefully, they can act as a counterbalance for the more sensation-based papers we currently often see in the general press." @default.
• W2545341229 created "2016-11-04" @default.
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• W2545341229 date "2016-10-20" @default.
• W2545341229 modified "2023-09-23" @default.
• W2545341229 title "Under the Magnifying Glass" @default.
• W2545341229 doi "https://doi.org/10.1002/qre.2100" @default.
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