Statistical Verification Framework for Platooning System of Systems with Uncertainty

Sang Hyun, Jiyoung Song, Seungchyul Shin, Doo-Hwan Bae
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引用次数: 9

Abstract

Platooning system is a well-known technology for alleviating traffic congestion and increasing fuel efficiency by grouping vehicles. It has the major characteristics of Systems of Systems (SoS), such as uncertainty. Several internal and external factors of uncertainty exist in the platooning system, such as car accidents, network disconnections, and simultaneous requests from other platoons. These factors make it difficult to guarantee that the system operates correctly in unpredictable scenarios and environments. The existing techniques used to verify the platooning system have two limitations: 1) the lack of consideration of uncertainty in scenarios and environments; 2) the application of exhaustive verification techniques which are vulnerable to the state-explosion problem. Thus, we suggest a statistical verification framework for a platooning SoS to address the above two limitations. The proposed framework automatically generates platooning configurations and scenarios with internal and external uncertain factors considered, and bypasses the state-explosion problem using a statistical verification technique. In this study, experimental results showed that the proposed approach generates 50% more valid scenarios than pure random strategy. In addition, we found two types of undiscovered failures and their causes in the VENTOS platooning system. These results indicate that our approaches enable the deep analysis of the platooning management system.
不确定系统队列系统的统计验证框架
队列行驶系统是一种众所周知的通过车辆分组来缓解交通拥堵和提高燃油效率的技术。它具有系统的系统(SoS)的主要特征,如不确定性。队列系统中存在一些内部和外部的不确定性因素,如车祸、网络中断、来自其他队列的同时请求等。这些因素使得难以保证系统在不可预测的场景和环境中正确运行。现有用于验证队列系统的技术存在两个局限性:1)缺乏对场景和环境的不确定性的考虑;2)穷尽验证技术的应用容易受到状态爆炸问题的影响。因此,我们提出了一个队列SoS的统计验证框架,以解决上述两个限制。该框架考虑了内部和外部不确定因素,自动生成队列配置和场景,并利用统计验证技术绕过状态爆炸问题。在本研究中,实验结果表明,该方法比纯随机策略产生的有效场景多50%。此外,我们还发现了两种未被发现的故障类型及其原因。这些结果表明,我们的方法能够对队列管理系统进行深入分析。
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