Perceived Time To Collision as Public Space Users' Discomfort Metric
Alireza Jafari, Yen-Chen Liu
TL;DR
This work targets the quantification of public-space discomfort caused by shared sidewalk use of micro-mobility devices. It introduces perceived Time To Collision ($T_p$) in 2D as a real-time, geometry-based discomfort proxy and tests it through controlled e-scooter–pedestrian experiments in a hallway. The results reveal a strong correlation between $T_p$ and reported discomfort when both agents can see each other, with median $T_p$ values of approximately 0.52 s for facing interactions and 1.24 s for passing interactions; the correlation weakens when visibility is absent. The findings support using $T_p$ for online discomfort estimation in ADAS and robotic systems and point to integrating this metric into control strategies to improve comfort in shared public spaces.
Abstract
Micro-mobility transport vehicles such as e-scooters are joining current sidewalk users and affect the safety and comfort of pedestrians as primary sidewalk users. The lack of agreed-upon metrics to quantify people's discomfort hinders shared public space safety research. We introduce perceived Time To Collision (TTC) as a potential metric of user discomfort performing controlled experiments using an e-scooter and a pedestrian moving in a hallway. The results strongly correlate the participant's reported discomfort and the perceived TTC. Therefore, TTC is a potential metric for public space users' discomfort. Since the metric only uses relative velocity and position information, it is a viable candidate for neighboring people's discomfort estimation in advanced driver assistance systems for e-scooters and PMVs. Our ongoing research extends the results to mobile robots.
