主页 / SAE 2018 自动驾驶汽车安全技术国际论坛 / 机器学习对高度自动驾驶功能安全系统的挑战
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作者Mark A. Crawford, Jr. @长城汽车
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简介
Can Machine Learning in Highly Automated Driving Exist in a Functional Safety System?
Mark A. Crawford, Jr. Great Wall Motor ABSTRACT Machine learning (ML) is increasingly becoming a key enabling technology for highly automated driving (HAD) vehicles. With all the significant advances that ML has contributed in HAD, there are significant challenges in assessing the risks associated with this artificial intelligence technology. ML presents unique hazards and software challenges that require new approaches to ensure functional safety. This presentation will review the difficulties in incorporating ML into HAD to reduce safety risks and will discuss recommendations for solving these problems in a functional safety context.
机器学习（ML）技术正日益成为推动高度自动驾驶（HAD）汽车发展的关键因素。不过，ML 技术在推动 HAD 汽车实现重大发展的同时，也带来了一些新的安全风险。具体来说，ML 技术的应用给汽车功能安全 带来了新风险与新的软件挑战。本演讲将侧重介绍ML 技术应用于HAD 汽车所带来的安全风险，并就如 何提高HAD 汽车功能安全提出了几点建议。
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援引http://www.sae.org.cn/events/avst?tab=278
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附件下载
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Mark.Crawford.Can.Machine.Learning.in.Highly.Automated.Driving.Exist.in.a.Functional.Safety.System?.pdf