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

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Abstract

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.

Bibliographical metadata

Original languageEnglish
JournalJournal of Sensor and Actuator Networks
DOIs
Publication statusPublished - 25 Jun 2021