Joint virtual-queue–based passing-sequence decision method for autonomous haul trucks at typical joint intersections in open-pit mines

Abstract Autonomous haul truck transportation in open-pit mines is gradually progressing from small-scale trials to large-scale deployment, and several large open-pit mines have already achieved regular unmanned haul truck operations. However, one of the key bottlenecks restricting further development is operational efficiency. Due to the limitations of current autonomous driving decision-making algorithms, conflicts between haul trucks frequently occur at critical intersections. Among them, joint intersections, as a typical complex intersection scenario, often experience severe congestion that requires manual remote intervention for resolution. To address this issue, this paper proposes a joint virtual-queue–based passing-sequence decision method for autonomous haul trucks at joint intersections. First, a joint virtual-queue–based passing-sequence generation algorithm is developed, which can stably generate conflict-free vehicle passing sequences across two adjacent intersections with computational efficiency suitable for real-time implementation. Second, a priority reallocation strategy that considers the load conditions of each entry lane is proposed to further enhance congestion mitigation capability under high-traffic conditions. Finally, a simulation test scenario of joint intersections is constructed using the SUMO software to verify the feasibility of the proposed method in achieving efficient and conflict-free vehicle passing in open-pit mine environments. The proposed approach provides an effective decision-making solution for alleviating congestion of autonomous haul trucks at joint intersections in open-pit mines.