The Halting problem: Video analysis of self-driving cars in traffic

要旨

Using publicly uploaded videos of the Waymo and Tesla FSD self-driving cars, this paper documents how self-driving vehicles still struggle with some basics of road interaction. To drive safely self-driving cars need to interact in traffic with other road users. Yet traffic is a complex, long established social domain. We focus on one core element of road interaction: when road users yield for each other. Yielding – slowing down for others in traffic – involves communication between different road users to decide who will ‘go’ and who will ‘yield’. Videos of the Waymo and Tesla FSD self-driving cars show how these systems fail to both yield for others, as well as failing to go when yielded to. In discussion, we explore how these ‘problems’ illustrate both the complexity of designing for road interaction, but also how the space of physical machine/human social interactions more broadly can be designed for.

受賞
Best Paper
著者
Barry Brown
Stockholm University, Stockholm, Sweden
Mathias Broth
Linköping University, Linköping, Sweden
Erik Vinkhuyzen
Nissan, Palo Alto, California, United States
論文URL

https://doi.org/10.1145/3544548.3581045

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: AI Trust, Transparency and Fairness

Room Y05+Y06
6 件の発表
2023-04-25 20:10:00
2023-04-25 21:35:00