An Empirical Study of Reliability Analysis for Platooning System-of-Systems

Sangwon Hyun,Lingjun Liu,Hansu Kim,Esther Cho,Doo-Hwan Bae

2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C)（2021）

Cited 1|Views24

Abstract

As a type of advanced autonomous vehicle software, platooning system-of-systems (SoS) has received tremendous attention as a next-generation system. Platooning SoS can attain several benefits, such as increasing fuel efficiency and alleviating traffic congestion by grouping autonomous vehicles in close prox-imity. Many studies have focused on analyzing the reliability of platooning SoS, as it is a safety-critical system. However, existing studies have two major limitations in their reliability analysis: (1) the studies did not fully cover the internal uncertainties of platooning SoS, such as heterogeneity; (2) they restricted external uncertainties by limiting the test scenarios to a single platoon, which could adversely affect the confidence of the analysis results. In addition, there exists no common fault dataset for the analysis of platooning SoS. Therefore, we provide an open dataset for platooning SoS by considering internal and external uncertainty factors during simulations. We empirically analyzed the execution logs of random platooning SoS scenarios in terms of reliability. We found 16 types of failure scenarios and root causes of the failures, as a result of the empirical study. Further, we generated the benchmark dataset, PLTBench, by classifying all failed logs based on the detected failure cases. We provide all the artifacts and descriptions in our benchmark web page as well as example codes to utilize the PLTBench. The conclusions of this study can enrich the general failure scenarios and experimental data set of platooning SoS for future studies.

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Key words

Autonomous vehicle system,Platooning System-of-Systems,Cyber-Physical system,Empirical study,Simulation-based Reliability analysis,Benchmark dataset

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