2023 article
Real-Time Scheduling of Autonomous Driving System with Guaranteed Timing Correctness
2023 IEEE 29TH REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM, RTAS, pp. 185–197.
TL;DR:
This paper formulates the AD system as a multi-rate DAG and proposes an integrated framework to co-analyze the schedulability of individual tasks and the end-to-end latency of task chains in the multi- rate DAG.
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(Web of Science)
Source: Web Of Science
Added: July 31, 2023
In the autonomous driving (AD) system, complex data dependencies exist between tasks with different activation rates, making it very hard to analyze systems’ real-time behaviors. This paper formulates the AD system as a multi-rate DAG and proposes an integrated framework to co-analyze the schedulability of individual tasks and the end-to-end latency of task chains in the multi-rate DAG. Integer linear programming (ILP) techniques are developed to guide how to drop redundant workload to increase the chance that timing requirements can be met. This paper proposed one analysis framework which enables an automated process in which designs of the AD system are created, analyzed and refined in an iterative way, i.e., the analysis result in the last iteration provides valuable guidance to redesign the AD system in the next iteration. Experiments are conducted to evaluate the performance of our analysis method.