This paper presents a framework, called VERIFCAR, devoted to the validation of decision policies of communicating autonomous vehicles (CAVs). The approach focuses on the formal modeling of CAVs by means of timed automata, allowing a formal and exhaustive analysis of the behaviors of vehicles. VERIFCAR supports a parametric modeling of CAV systems as a network of timed automata tailored for verification and limiting the well-known state space explosion. As an illustration, VERIFCAR is applied to check robustness and efficiency, as well as to asses the impact of communication delays on the decision algorithms of CAVs, on well chosen case studies representing real-life critical situations.

MIRELA is a high-level language and a rapid prototyping framework dedicated to systems where virtual and digital objects coexist in the same environment and interact in real time. Its semantics is given in the form of networks of timed automata, which can be checked using symbolic methods. This paper shows how to detect various kinds of indefinite waitings in the components of such systems. The method is experimented using the PRISM model checker.Comment: In Proceedings ESSS 2015, arXiv:1506.0325

Autonomous vehicles' behavioural analysis represents a major challenge in the automotive world. In order to ensure safety and fluidity of driving, various methods are available, in particular, simulation and formal verification. The analysis, however, has to cope with very complex environments depending on many parameters evolving in real time. In this context, none of the aforementioned approaches is fully satisfactory, which lead us to propose a combined methodology in order to point out suspicious behaviours more efficiently. We illustrate this approach by studying a non deterministic scenario involving a vehicle, which has to react to some perilous situation.

Mixed reality systems overlay real data with virtual information in order to assist users in their current task; they are used in many fields (surgery, maintenance, entertainment,...). Such systems generally combine several hardware components operating at different time scales, and software that has to cope with these timing constraints. MIRELA, for MIxed REality LAnguage, is a framework aimed at modelling, analysing and implementing systems composed of sensors, processing units, shared memories and rendering loops, communicating in a welldefined manner and submitted to timing constraints. The paper describes how harmful software behaviour, which may result in possible hardware deterioration or revert the system's primary goal from user assistance to user impediment, may be detected such as (global and local) deadlocks or starvation features. This also includes a study of temporal properties resulting in a finer understanding of the software timing behaviour, in order to fix it if needed.

This paper presents a method for the validation of communicating autonomous vehicles (CAVs) systems. The approach focuses on the formal modeling of CAVs by means of timed automata, to allow the formal analysis through model-checkers of the vehicle behavior, including their fault tolerance due to various kinds of injected faults. We also present our case studies results, based on implementations of our CAVs' model in UPPAAL.

Timed automata are a common formalism for the verification of concurrent systems subject to timing constraints. They extend finite-state automata with clocks, that constrain the system behavior in locations, and to take transitions. While timed automata were originally designed for safety (in the wide sense of correctness w.r.t. a formal property), they were progressively used in a number of works to guarantee security properties. In this work, we review works studying security properties for timed automata in the last two decades. We notably review theoretical works, with a particular focus on opacity, as well as more practical works, with a particular focus on attack trees and their extensions. We derive main conclusions concerning open perspectives, as well as tool support.

Mixed reality systems overlay real data with virtual information in order to assist users in their current task. They generally combine several hardware components operating at different time scales, and software that has to cope with these timing constraints. MIRELA, for MIxed REality LAnguage, is a framework aimed at modelling, analysing and implementing systems composed of sensors, processing units, shared memories and rendering loops, communicating in a well-defined manner and submitted to timing constraints. The framework is composed of (i) a language allowing a high level, and partially abstract, specification of a concurrent real-time system, (ii) the corresponding semantics, which defines the translation of the system to concrete networks of timed automata, (iii) a methodology for analysing various real-time properties, and (iv) an implementation strategy. We present here a summary of several of our papers about this framework, as well as some recent extensions concerning probability and non-deterministic choices.

We formalise and study multi-agent timed models MAPTs (Multi-Agent with Periodic timed Tasks), where each agent is associated with a regular timed schema upon which all possible actions of the agent rely. MAPTs allow for an accelerated semantics and a layered structure of the state space, so that it is possible to explore the latter dynamically and use heuristics to greatly reduce the computation time needed to address reachability problems. We use an available tool for the Petri net implementation of MAPTs, to explore the state space of autonomous vehicle systems. Then, we compare this exploration with timed automata-based approaches in terms of expressiveness of available queries and computation time.