An eye-movement-based predicted trajectory guidance control (ePTGC) is proposed to mitigate the maneuverability degradation of a teleoperated ground vehicle caused by communication delays. Human sensitivity to delays is the main reason for the performance degradation of a ground vehicle teleoperation system. The proposed framework extracts human intention from eye-movement. Then, it combines it with contextual constraints to generate an intention-compliant guidance trajectory, which is then employed to control the vehicle directly. The advantage of this approach is that the teleoperator is removed from the direct control loop by using the generated trajectories to guide vehicle, thus reducing the adverse sensitivity to delay. The delay can be compensated as long as the prediction horizon exceeds the delay. A human-in-loop simulation platform is designed to evaluate the teleoperation performance of the proposed method at different delay levels. The results are analyzed by repeated measures ANOVA, which shows that the proposed method significantly improves maneuverability and cognitive burden at large delay levels (>200 ms). The overall performance is also much better than the PTGC which does not employ the eye-movement feature.

翻译：提出了一种基于眼动的预瞄轨迹引导控制方法（ePTGC），用于缓解通信时延导致的遥操作地面车辆机动性能退化。人类对时延的敏感性是造成地面车辆遥操作系统性能下降的主要原因。该框架通过眼动提取人类意图，结合环境约束生成符合意图的引导轨迹，并直接用于控制车辆。该方法的优势在于利用生成的轨迹引导车辆，将遥操作者从直接控制回路中移除，从而降低对时延的敏感度。只要预测时域超过通信时延，即可实现时延补偿。设计了人在环仿真平台，在不同时延水平下评估所提方法的遥操作性能。通过重复测量方差分析（ANOVA）对结果进行统计检验，表明该方法在大时延（>200 ms）条件下能显著提升机动性能并降低认知负荷；整体性能亦远优于未采用眼动特征的PTGC方法。