用预测力场模型提升机器人行人的安全与舒适性
Empirical Pedestrian Safety Assessment in a Mobile Robot Using a Predictive Social Force Model
- 引入预测社会力模型，在有限时域内预测行人互动
- PTTC集成使客观安全指标显著提升，最小碰撞时间改善18%
- 预测虽未显著提升主观感受，但对单人场景有潜在优化价值
移动机器人将与行人共享人行道，需兼顾客观安全与主观舒适。计算高效的社交力模型（SFM）为动态人群中的实时导航提供可解释方案。近期将投影碰撞时间（PTTC）融入SFM变体（如TSFM）提升了安全指标，但预测能力的影响尚不明确。本文提出预测型SFM（PSFM）和预测型TSFM（PTSFM），通过在有限时间窗口内整合预测的社交力向量实现改进。在非完整约束移动机器人上实现SFM、TSFM、PSFM与PTSFM，并邀请志愿者参与面对面交互实验，系统评估各方法的客观与主观安全性。客观安全以最小PTTC、平均速度、最小距离、侧向距离及最大轨迹曲率衡量；主观安全通过李克特量表问卷评估舒适度、流畅性、距离恰当性与速度适宜性。结果表明，PTTC集成显著改善了安全指标；预测部分贡献有限，仅在某些子指标中略有显现。部分参与者感知预测方法运动更平滑、速度更安全，但曼-惠特尼检验显示主观评分无显著差异。因此，基于PTTC的导航有效提升安全，而提出的预测机制在单行人场景中增益有限。
原文摘要 · Abstract (English)
Mobile robots are going to share the sidewalks with pedestrians. They must ensure their objective safety and respect the walkers' subjective safety/comfort. Computationally efficient Social Force Models (SFM) present interpretable solutions for real-time robot navigation in dynamic crowds. Recent explorations of Projected Time-to-collision (PTTC) integration into SFM variants, for example, PTTC-based SFM (TSFM), improve safety metrics. But the effect of predictive variants is unclear. We introduce Predictive SFM (PSFM) and Predictive TSFM (PTSFM) by integrating predicted social force vectors over a finite time horizon. The paper implements SFM, TSFM, PSFM, and PTSFM on a nonholonomic mobile robot and performs experimental trials with volunteers attending a facing scenario. We systematically study objective and subjective safety across the variants. Minimum PTTC, average speed, minimum distance, lateral distance, and the maximum trajectory curvature benchmark the objective safety. Likert scale post-interaction surveys assess subjective safety by marking comfort, smoothness, distance appropriateness, and speed suitability. We confirm that PTTC integration improves safety metrics. The prediction contribution is limited and occasionally visible in some of the sub-metrics. Some participants perceive smoother movements and safer speed behavior with predictive methods, but Mann-Whitney tests reveal no significant differences in subjective ratings. Therefore, PTTC-based navigation enhances safety, whereas the formulated prediction offers limited additional benefits in single-pedestrian scenarios.
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