Search-based Generation of Waypoints for Triggering Self-Adaptations in Maritime Autonomous Vessels

TL;DR

This paper introduces WPgen, a search-based method using multi-objective optimization to generate waypoint modifications that trigger self-adaptations in maritime autonomous vessels, aiding in validation and safety assurance.

Contribution

It presents a novel multi-objective search approach, WPgen, for generating waypoint modifications to test self-adaptation triggers in maritime AV navigation software.

Findings

WPgen effectively identifies waypoint modifications that cause navigation issues.

Performance varies across different vessel types and WPgen variations.

Compared to random search, WPgen provides more targeted and effective test cases.

Abstract

Self-adaptation in maritime autonomous vessels (AVs) enables them to adapt their behaviors to address unexpected situations while maintaining dependability requirements. During the design of such AVs, it is crucial to understand and identify the settings that should trigger adaptations, enabling validation of their implementation. To this end, we focus on the navigation software of AVs, which must adapt their behavior during operation through adaptations. AVs often rely on predefined waypoints to guide them along designated routes, ensuring safe navigation. We propose a multiobjective search-based approach, called WPgen, to generate minor modifications to the predefined set of waypoints, keeping them as close as possible to the original waypoints, while causing the AV to navigate inappropriately when navigating with the generated waypoints. WPgen uses NSGA-II as the multi-objective search algorithm with three seeding strategies for its initial population, resulting in three variations of WPgen. We evaluated these variations on three AVs (one overwater tanker and two underwater). We compared the three variations of WPgen with Random Search as the baseline and with each other. Experimental results showed that the effectiveness of these variations varied depending on the AV. Based on the results, we present the research and practical implications of WPgen.