Evaluation of Coordination Strategies for Underground Automated Vehicle Fleets in Mixed Traffic

TL;DR

This paper evaluates adaptive coordination strategies for underground automated vehicle fleets in mixed traffic, introducing a new metric to predict efficiency and safety, and analyzing the impact of tunnel network features.

Contribution

It proposes a novel Path Overlap Density metric and assesses how coordination strategies and tunnel features affect AV fleet performance in underground environments.

Findings

Coordination strategies significantly influence safety and efficiency.

Map features are critical for optimizing AV performance.

Adaptive strategies are essential for safe underground operations.

Abstract

This study investigates the efficiency and safety outcomes of implementing different adaptive coordination models for automated vehicle (AV) fleets, managed by a centralized coordinator that dynamically responds to human-controlled vehicle behavior. The simulated scenarios replicate an underground mining environment characterized by narrow tunnels with limited connectivity. To address the unique challenges of such settings, we propose a novel metric - Path Overlap Density (POD) - to predict efficiency and potentially the safety performance of AV fleets. The study also explores the impact of map features on AV fleets performance. The results demonstrate that both AV fleet coordination strategies and underground tunnel network characteristics significantly influence overall system performance. While map features are critical for optimizing efficiency, adaptive coordination strategies are essential for ensuring safe operations.