Safe and Secure Support for Public Safety Networks

International audienceAs explained by Tanzi et al. in the first volume of this book, communicating and autonomous devices will surely have a role to play in the future Public Safety Networks. The “communicating” feature comes from the fact that the information should be delivered in a fast way to rescuers. The “autonomous” characteristic comes from the fact that rescuers should not have to concern themselves about these objects: they should perform their mission autonomously so as not to delay the intervention of the rescuers, but rather to assist them efficiently and reliably.</p

Using Formal Methods for Autonomous Systems: Five Recipes for Formal Verification

Formal Methods are mathematically-based techniques for software design and engineering, which enable the unambiguous description of and reasoning about a system's behaviour. Autonomous systems use software to make decisions without human control, are often embedded in a robotic system, are often safety-critical, and are increasingly being introduced into everyday settings. Autonomous systems need robust development and verification methods, but formal methods practitioners are often asked: Why use Formal Methods for Autonomous Systems? To answer this question, this position paper describes five recipes for formally verifying aspects of an autonomous system, collected from the literature. The recipes are examples of how Formal Methods can be an effective tool for the development and verification of autonomous systems. During design, they enable unambiguous description of requirements; in development, formal specifications can be verified against requirements; software components may be synthesised from verified specifications; and behaviour can be monitored at runtime and compared to its original specification. Modern Formal Methods often include highly automated tool support, which enables exhaustive checking of a system's state space. This paper argues that Formal Methods are a powerful tool for the repertoire of development techniques for safe autonomous systems, alongside other robust software engineering techniques.Comment: Accepted at Journal of Risk and Reliabilit

Certification Basis for a Fully Autonomous Uncrewed Passenger Carrying Urban Air Mobility Aircraft

The Urban Air Mobility campaign has set a goal to efficiently transport passengers and cargo in urban areas of operation with autonomous aircraft. This concept of operations will require aircraft to utilize technology that currently does not have clear regulatory requirements. This report contains a comprehensive analysis and creation of a certification basis for a fully autonomous uncrewed passenger carrying rotorcraft for use in Urban Air Mobility certified under Title 14 Code of Federal Regulations Part 27. Part 27 was first analyzed to determine the applicability of current regulations. The fully electric propulsion system and fully autonomous flight control system pose the largest gaps in current airworthiness standards. Part 27 regulations contained 241 directly applicable regulations, 47 regulations were not applicable, primarily due to being “human-centric”, and 34 regulations requiring special conditions. Once these gaps were identified, the extant literature related to autonomous and electric propulsion systems were utilized to propose special conditions and amendments to complete a certification basis for the notional rotorcraft. Amendments were also created to provide suggested regulatory changes to enhance applicability for future autonomous and electric rotorcraft seeking certification under 14 CFR Part 27. The proposed special conditions and amendments aid in the certification, safety, and proliferation of a fully autonomous and electric future

Supporting Validation of UAV Sense-and-Avoid Algorithms with Agent-Based Simulation and Evolutionary Search

A Sense-and-Avoid (SAA) capability is required for the safe integration of Unmanned Aerial Vehicles (UAVs) into civilian airspace. Given their safety-critical nature, SAA algorithms must undergo rigorous verification and validation before deployment. The validation of UAV SAA algorithms requires identifying challenging situations that the algorithms have difficulties in handling. By building on ideas from Search-Based Software Testing, this thesis proposes an evolutionary-search-based approach that automatically identifies such situations to support the validation of SAA algorithms. Specifically, in the proposed approach, the behaviours of UAVs under the control of selected SAA algorithms are examined with agent-based simulations. Evolutionary search is used to guide the simulations to focus on increasingly challenging situations in a large search space defined by (the variations of) parameters that configure the simulations. An open-source tool has been developed to support the proposed approach so that the process can be partially automated. Positive results were achieved in a preliminary evaluation of the proposed approach using a simple two-dimensional SAA algorithm. The proposed approach was then further demonstrated and evaluated using two case studies, applying it to a prototype of an industry-level UAV collision avoidance algorithm (specifically, ACAS XU) and a multi-UAV conflict resolution algorithm (specifically, ORCA-3D). In the case studies, the proposed evolutionary-search-based approach was empirically compared with some plausible rivals (specifically, random-search-based approaches and a deterministic-global-search-based approach). The results show that the proposed approach can identify the required challenging situations more effectively and efficiently than the random-search-based approaches. The results also show that even though the proposed approach is a little less competitive than the deterministic-global-search-based approach in terms of effectiveness in relatively easy cases, it is more effective and efficient in more difficult cases, especially when the objective function becomes highly discontinuous. Thus, the proposed evolutionary-search-based approach has the potential to be used for supporting the validation of UAV SAA algorithms although it is not possible to show that it is the best approach

Formal Methods for the Certification of Autonomous Unmanned Aircraft Systems

Abstract. In this paper we assess the feasibility of using formal methods, and model checking in particular, for the certification of Unmanned Aircraft Systems (UAS) within civil airspace. We begin by modelling a basic UAS control system in PROMELA, and verify it against a selected subset of the CAA’s Rules of the Air using the SPIN model checker. Next we build a more advanced UAS control system using the autonomous agent language Gwendolen, and verify it against the small subset of the Rules of the Air using the agent model checker AJPF. We introduce more advanced autonomy into the UAS agent and show that this too can be verified. Finally we compare and contrast the various approaches, discuss the paths towards full certification, and present directions for future research