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首页> 外文会议>International Symposium on Model-Based Safety and Assessment >Adaptive Error and Sensor Management for Autonomous Vehicles: Model-Based Approach and Run-Time System
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Adaptive Error and Sensor Management for Autonomous Vehicles: Model-Based Approach and Run-Time System

机译：自动车辆的自适应误差和传感器管理：基于模型的方法和运行时系统

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摘要

Over the past few years semi-autonomous driving functionality was introduced in the automotive market, and this trend continues towards fully autonomous cars. While in autonomous vehicles data from various types of sensors realize the new highly safety critical autonomous functionality, the already complex system architecture faces the challenge of designing highly reliable and safe autonomous driving system. Since sensors are prone to intermittent faults, using different sensors is better and more cost effective than duplicating the same sensor type because of diversity of reaction of different sensor typesto the same environmental condition. Specifying and validating sensors and providing technical means that enable usage of data from different sensors in case of failures is a challenging, time-consuming and error-prone task for engineers. Therefore, in this paper we present our model-based approach and a runtime system that improves the safety of autonomous driving systems by providing reusable framework managing different sensor setups in a vehicle in a case of a error. Moreover, the solution that we provide enables adaptive graceful degradation and reconfiguration by effective use of the system resources. At the end we explain in an example when and how the approach can be applied.
机译：在过去的几年里，汽车市场引入了半自动驾驶功能，这一趋势持续到全统自动的汽车。虽然在来自各种类型的传感器的自动车辆数据中实现了新的高度安全的关键自主功能，但已经复杂的系统架构面临着设计高度可靠和安全的自主驱动系统的挑战。由于传感器容易受到间歇性故障，因此使用不同的传感器比不同传感器的反应的多样性更好，更具成本效益，而不是复制相同的传感器类型，因为不同传感器的反应相同的环境条件。指定和验证传感器并提供技术意味着在故障情况下使来自不同传感器的数据能够使用不同传感器的数据是工程师的具有挑战性，耗时和错误的任务。因此，在本文中，我们介绍了我们基于模型的方法和运行时系统，通过提供在错误的情况下提供管理不同传感器设置的可重复使用的框架来提高自动驾驶系统的安全性。此外，我们提供的解决方案通过有效使用系统资源，可以实现适应性的优常劣化和重新配置。最后，我们在示例以及如何应用方法时解释。

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