MineSim: A scenario-based simulation test system and benchmark for autonomous trucks in open-pit mines

Abstract

Simulation environments are essential for validating algorithms, evaluating system performance, and ensuring safety in autonomous driving systems before real-world deployment. Existing autonomous driving simulators are designed for urban scenarios but lack coverage of unstructured road environments in open-pit mining. This paper introduces MineSim, an open-source, scenario-based simulation test system specifically developed for planning tasks in autonomous trucks operating in open-pit mines. MineSim includes several components: automated scenario parsing, state update models for the ego vehicle, state update policies for other agents, metric evaluation, and scenario visualization tools. It incorporates numerous real-world traffic scenarios from two open-pit mines that capture the unique challenges of unstructured road environments, including irregular intersections, roads without clear lane markings, and the response lags of heavy autonomous mining trucks. Furthermore, MineSim provides scenario libraries and benchmarks for static and dynamic obstacle avoidance problems, facilitating research into planning algorithms in these complex settings. By offering reproducible testing methods and scenario data, MineSim serves as a critical resource for advancing autonomous driving technologies in non-urban and unstructured road environments (see https://buaa-trans-mine-group.github.io/minesim).