Having systems that can adapt themselves in case of faults or changing environmental conditions is of growing interest for industry and especially for the automotive industry considering autonomous driving. In autonomous driving, it is vital to have a system that is able to cope with faults in order to enable the system to reach a safe state. In this paper, we present an adaptive control method that can be used for this purpose. The method selects alternative actions so that given goal states can be reached, providing the availability of a certain degree of redundancy. The action selection is based on weight models that are adapted over time, capturing the success rate of certain actions. Besides the method, we present a Java implementation and its validation based on two case studies motivated by the requirements of the autonomous driving domain. We show that the presented approach is applicable both in case of environmental changes but also in case of faults occurring during operation. In the latter case, the methods provide an adaptive behavior very much close to the optimal selection.

中文翻译：

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自动驾驶自适应系统

拥有能够在出现故障或不断变化的环境条件下自行调整的系统越来越引起工业界的兴趣，尤其是考虑自动驾驶的汽车工业。在自动驾驶中，拥有一个能够应对故障的系统至关重要，这样系统才能达到安全状态。在本文中，我们提出了一种可用于此目的的自适应控制方法。该方法选择替代动作，以便可以达到给定的目标状态，提供一定程度的冗余可用性。动作选择基于随时间调整的权重模型，捕获某些动作的成功率。除了该方法之外，我们还基于由自动驾驶领域的要求驱动的两个案例研究，提出了 Java 实现及其验证。我们表明，所提出的方法既适用于环境变化，也适用于运行期间发生的故障。在后一种情况下，这些方法提供了非常接近最佳选择的自适应行为。