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首页> 外文会议>IAAI-12;Innovative applications of artificial intelligence conference;AAAI conference on artificial intelligence;Symposium on educational advances in artificial intelligence;AAAI-12;EAAI-12 >Learning Driver's Behavior to Improve the Acceptance of Adaptive Cruise Control
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Learning Driver's Behavior to Improve the Acceptance of Adaptive Cruise Control

机译：学习驾驶员的行为以提高自适应巡航控制的接受度

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摘要

Adaptive Cruise Control (ACC) is a technology that allows a vehicle to automatically adjust its speed to maintain a preset distance from the vehicle in front of it based on the driver's preferences. Individual drivers have different driving styles and preferences. Current systems do not distinguish among the users. We introduce a method to combine machine learning algorithms with demographic information and expert advice into existing automated assistive systems. This method can save on the interactions between drivers and automated systems by adjusting parameters relevant to the operation of these systems based on their specific drivers and context of drive. We also learn when users tend to engage and disengage the automated system. This method sheds light on the kinds of dynamics that users develop while interacting with automation and can teach us how to improve these systems for the benefit of their users. While accepted packages such as Weka were successful in learning drivers' behavior, we found that improved learning models could be developed by adding information on drivers' demographics and a previously developed model about different driver types. We present the general methodology of our learning procedure and suggest applications of our approach to other domains as well.
机译：自适应巡航控制（ACC）技术使车辆能够根据驾驶员的喜好自动调节其速度，以保持与前方车辆的预设距离。各个驾驶员具有不同的驾驶方式和偏好。当前的系统不能在用户之间进行区分。我们介绍一种将机器学习算法与人口统计信息和专家建议相结合的方法，并将其结合到现有的自动化辅助系统中。通过根据特定系统的驱动程序和驱动器上下文调整与这些系统的操作相关的参数，此方法可以节省驱动程序和自动化系统之间的交互。我们还学习用户何时倾向于使用和退出自动化系统。该方法阐明了用户在与自动化交互时开发的各种动态，并且可以教会我们如何为用户的利益而改进这些系统。尽管Weka等已被接受的软件包成功地学习了驾驶员的行为，但我们发现可以通过添加有关驾驶员的人口统计信息和以前开发的有关不同驾驶员类型的模型来开发改进的学习模型。我们介绍了学习过程的一般方法，并建议了我们的方法在其他领域的应用。

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