Formal Development of Safe Automated Driving Using Differential Dynamic Logic

Selvaraj, Yuvaraj; Ahrendt, Wolfgang; Fabian, Martin

doi:10.1109/tiv.2022.3204574

Cited by 8 publications

(1 citation statement)

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“…However, it can give more interesting results as it takes into account the links between the dynamics and the values of a system, while previous methods had the drawback of separating the two aspects. In terms of applications, qualitative reasoning mainly allows formal computation and proof using temporal logic [16], diagnosis [17], [18], verification [19], [20] and approximation [21]. Qualitative modeling implies reasoning on multiple levels of abstraction.…”

Section: Introductionmentioning

confidence: 99%

Qualitative Reasoning and Cyber-Physical Systems: Abstraction, Modeling, and Optimized Simulation

Gueuziec,

Gallois,

Boulanger

2023

2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)

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Complex systems modeling and simulation are critical in many industrial and research fields and specifically to predict, prove, verify, and understand the behavior of cyberphysical systems. The diversity of variables in a system creates complexity [1] and a need for more efficient modeling and simulation methods. In the case of hybrid systems [2], the heterogeneity of the discrete and continuous parts makes these tasks more challenging by adding the necessity to manage different types of variables and transitions separately. Qualitative reasoning offers a paradigm to study the behavior of such systems with a high level of abstraction, trading precision and specificity against generality and formalism. This paradigm can be preferred to numerical analysis in specific situations, especially in the upstream study of a system, in its design phases. However, the different representations and the various contexts of such systems create an important obstacle to define a general methodology for applying qualitative reasoning and modeling to every case. In this article, we propose a method and a tool to unify different qualitative reasoning techniques on complex cyber-physical systems. We will also develop the possibilities offered by the obtained abstraction in various tasks such as formal proof, verification, property analysis, diagnosis, simulation driving, and system monitoring.

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