Portable RK: A Portable Resource Kernel for Guaranteed and Enforced Timing Behavior
RTAS '99 Proceedings of the Fifth IEEE Real-Time Technology and Applications Symposium
Elastic Task Model for Adaptive Rate Control
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Model-Based Development of Embedded Systems: The SysWeaver Approach
RTAS '06 Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium
Autonomous driving in urban environments: Boss and the Urban Challenge
Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part I
A Gravitational Task Model for Target Sensitive Real-Time Applications
ECRTS '08 Proceedings of the 2008 Euromicro Conference on Real-Time Systems
Rhythmic Tasks: A New Task Model with Continually Varying Periods for Cyber-Physical Systems
ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
SAFER: System-level Architecture for Failure Evasion in Real-time Applications
RTSS '12 Proceedings of the 2012 IEEE 33rd Real-Time Systems Symposium
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Autonomous driving technologies have been emerging over the past few years, and semi-autonomous driving functionalities have been deployed to vehicles available in the market. Since autonomous driving is realized by the intelligent processing of data from various types of sensors such as LIDAR, radar, camera, etc., the complexity of designing a dependable real-time autonomous driving system is rather high. Although there has been much research on building a reliable real-time system using hardware replication, the resulting systems tend to add significant extra cost due to hardware replication. Therefore, an alternative solution would be helpful in building an autonomous vehicle in a cost-effective way. An autonomous driving system is different from the conventional reliable real-time system because it requires (1) flexible design, (2) adaptive graceful degradation and (3) effective use of different modalities of sensors and actuators. To address these characteristics, we summarize SAFER (System-level Architecture for Failure Evasion in Real-time applications) our previous work on flexible system design. We then present a conceptual framework for autonomous vehicles to provide adaptive graceful degradation and support for using different types of sensors/actuators when a failure happens. We motivate our proposed framework with various scenarios, and we describe how SAFER can be extended to support the proposed conceptual framework.