Run-Time Adaptive Error and State Management for Open Automotive Systems

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. A common approach to build a reliable real-time system is using hardware replication, however the solution tends to be very costly. An alternative approach is providing support for adaptive error and effective resource management that allows a system to adapt and reconfigure after failures of part of the system without requiring the user intervention. In addition, the end-customer is used to the possibility of easy personalization or extensibility of the electronic systems with new HW or SW. In this paper we present our model-based framework and run-time system that enables system extension and improves the safety of autonomous driving systems by providing reusable formal scheme enabling adaptive error and resource management. A case study explaining when and how the approach can be applied is also presented.