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Article

A Double-Level Model Checking Approach for an Agent-Based Autonomous Vehicle and Road Junction Regulations

1
Graduate Program in Computer Science (PPGCC), Federal University of Technology—Parana (UTFPR), Ponta Grossa 84017-220, PR, Brazil
2
Department of Computer Science, University of Manchester, Manchester M13 9PL, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Claudio Savaglio, Daniela Briola, Rafael C. Cardoso, Angelo Ferrando, Claudio Menghi and Tobias Ahlbrecht
J. Sens. Actuator Netw. 2021, 10(3), 41; https://doi.org/10.3390/jsan10030041
Received: 15 March 2021 / Revised: 18 June 2021 / Accepted: 21 June 2021 / Published: 25 June 2021
(This article belongs to the Special Issue Agents and Robots for Reliable Engineered Autonomy)
Usually, the design of an Autonomous Vehicle (AV) does not take into account traffic rules and so the adoption of these rules can bring some challenges, e.g., how to come up with a Digital Highway Code which captures the proper behaviour of an AV against the traffic rules and at the same time minimises changes to the existing Highway Code? Here, we formally model and implement three Road Junction rules (from the UK Highway Code). We use timed automata to model the system and the MCAPL (Model Checking Agent Programming Language) framework to implement an agent and its environment. We also assess the behaviour of our agent according to the Road Junction rules using a double-level Model Checking technique, i.e., UPPAAL at the design level and AJPF (Agent Java PathFinder) at the development level. We have formally verified 30 properties (18 with UPPAAL and 12 with AJPF), where these properties describe the agent’s behaviour against the three Road Junction rules using a simulated traffic scenario, including artefacts like traffic signs and road users. In addition, our approach aims to extract the best from the double-level verification, i.e., using time constraints in UPPAAL timed automata to determine thresholds for the AVs actions and tracing the agent’s behaviour by using MCAPL, in a way that one can tell when and how a given Road Junction rule was selected by the agent. This work provides a proof-of-concept for the formal verification of AV behaviour with respect to traffic rules. View Full-Text
Keywords: Rules of the Road; Autonomous Vehicles; agents; model checking Rules of the Road; Autonomous Vehicles; agents; model checking
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MDPI and ACS Style

Alves, G.V.; Dennis, L.; Fisher, M. A Double-Level Model Checking Approach for an Agent-Based Autonomous Vehicle and Road Junction Regulations. J. Sens. Actuator Netw. 2021, 10, 41. https://doi.org/10.3390/jsan10030041

AMA Style

Alves GV, Dennis L, Fisher M. A Double-Level Model Checking Approach for an Agent-Based Autonomous Vehicle and Road Junction Regulations. Journal of Sensor and Actuator Networks. 2021; 10(3):41. https://doi.org/10.3390/jsan10030041

Chicago/Turabian Style

Alves, Gleifer V., Louise Dennis, and Michael Fisher. 2021. "A Double-Level Model Checking Approach for an Agent-Based Autonomous Vehicle and Road Junction Regulations" Journal of Sensor and Actuator Networks 10, no. 3: 41. https://doi.org/10.3390/jsan10030041

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