Erik Vinkhuyzen

We compare two types of situations involving monitoring of car driving: a driving instructor overseeing a trainee driver and a safety driver overseeing the performance of autonomous vehicle (AV) software. Our focus is on instances of monitoring that precede (1) interventions that are aborted before impacting the driving and (2) actual interventions on the driving in these two different settings. We find that in both cases the monitoring party “waits and sees” whether each type of “driving agent” will notice the impending trouble and adjust the driving appropriately. However, there are also marked differences: In the case of a driving instructor, the monitoring and intervening is a socially accountable event that may be responded to by the trainee driver, while in the case of an autonomous vehicle there are no such considerations, resulting in a difference in how the monitoring activity is embodied.

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 – such as by 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.

The advent of autonomous cars creates a range of new questions about road safety, as well as a new collaborative domain for CSCW to analyse. This paper uses video data collected from five countries - India, Spain, France, Chile, and the USA - to study how road users interact with each other. We use interactional video analysis to document how co-ordination is achieved in traffic not just through the use of formal rules, but through situated communicative action. Human movement is a rich implicit communication channel and this communication is essential for safe manoeuvring on the road, such as in the co-ordination between pedestrians and drivers. We discuss five basic movements elements: gaps, speed, position, indicating and stopping. Together these elements can be combined to make and accept offers, show urgency, make requests and display preferences. We build on these results to explore lessons for how we can design the implicit motion of self-driving cars so that these motions are understandable - in traffic - by other road users. In discussion, we explore the lessons from this for designing the movement of robotic systems more broadly.