{"title":"Statistical verification of autonomous system controllers under timing uncertainties","authors":"","doi":"10.1007/s11241-023-09417-x","DOIUrl":null,"url":null,"abstract":"<h3>Abstract</h3> <p>Software in autonomous systems like autonomous cars, robots or drones is often implemented on resource-constrained embedded systems with heterogeneous architectures. At the heart of such software are multiple feedback control loops, whose dynamics not only depend on the control strategy being used, but also on the timing behavior the control software experiences. But performing timing analysis for safety critical control software tasks, particularly on heterogeneous computing platforms, is challenging. Consequently, a number of recent papers have addressed the problem of <em>stability analysis</em> of feedback control loops in the presence of timing uncertainties (<em>cf.</em>, deadline misses). In this paper, we address a different class of safety properties, <em>viz.</em>, whether the system trajectory with timing uncertainties deviates too much from the nominal trajectory. Verifying such <em>quantitative</em> safety properties involves performing a reachability analysis that is computationally intractable, or is too conservative. To alleviate these problems we propose to provide statistical guarantees over the behavior of control systems with timing uncertainties. More specifically, we present a Bayesian hypothesis testing method that estimates deviations from a nominal or ideal behavior. We show that our analysis can provide, with high confidence, tighter estimates of the deviation from nominal behavior than using known reachability analysis methods. We also illustrate the scalability of our techniques by obtaining bounds in cases where reachability analysis fails, thereby establishing the practicality of our proposed method.</p>","PeriodicalId":54507,"journal":{"name":"Real-Time Systems","volume":"45 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Real-Time Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s11241-023-09417-x","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Software in autonomous systems like autonomous cars, robots or drones is often implemented on resource-constrained embedded systems with heterogeneous architectures. At the heart of such software are multiple feedback control loops, whose dynamics not only depend on the control strategy being used, but also on the timing behavior the control software experiences. But performing timing analysis for safety critical control software tasks, particularly on heterogeneous computing platforms, is challenging. Consequently, a number of recent papers have addressed the problem of stability analysis of feedback control loops in the presence of timing uncertainties (cf., deadline misses). In this paper, we address a different class of safety properties, viz., whether the system trajectory with timing uncertainties deviates too much from the nominal trajectory. Verifying such quantitative safety properties involves performing a reachability analysis that is computationally intractable, or is too conservative. To alleviate these problems we propose to provide statistical guarantees over the behavior of control systems with timing uncertainties. More specifically, we present a Bayesian hypothesis testing method that estimates deviations from a nominal or ideal behavior. We show that our analysis can provide, with high confidence, tighter estimates of the deviation from nominal behavior than using known reachability analysis methods. We also illustrate the scalability of our techniques by obtaining bounds in cases where reachability analysis fails, thereby establishing the practicality of our proposed method.
期刊介绍：
Papers published in Real-Time Systems cover, among others, the following topics: requirements engineering, specification and verification techniques, design methods and tools, programming languages, operating systems, scheduling algorithms, architecture, hardware and interfacing, dependability and safety, distributed and other novel architectures, wired and wireless communications, wireless sensor systems, distributed databases, artificial intelligence techniques, expert systems, and application case studies. Applications are found in command and control systems, process control, automated manufacturing, flight control, avionics, space avionics and defense systems, shipborne systems, vision and robotics, pervasive and ubiquitous computing, and in an abundance of embedded systems.
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