For instructions on how to apply, please see: PhD Studentships: UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents.
- Steve Brewster: School of Computing Science
- Frank Pollick: School of Psychology
Automated vehicles must share the road with pedestrians and cyclists, and drive safely around them. Autonomous cars, therefore, must have some form of social intelligence if they are to function correctly around other road users. There has been work looking at how pedestrians may interact with future autonomous vehicles [ROT15] and potential solutions have been proposed (e.g. displays on the outside of cars to indicate that the car has seen the pedestrian). However, there has been little work on automated cars and cyclists. When there is no driver in the car, social cues such as eye contact, waving, etc., are lost [ROT15]. This changes the social interaction between the car and the cyclist, and may cause accidents if it is no longer clear, for example, who should proceed. Automated cars also behave differently to cars driven by humans, e.g. they may appear more cautious in their driving, which the cyclist may misinterpret. The aim of this project is to study the social cues used by drivers and cyclists, and create multimodal solutions that can enable safe cycling around autonomous vehicles. The first stage of the work will be observation of the communication between human drivers and cyclists through literature review and fieldwork. The second stage will be to build a bike into our driving simulator [MAT19] so that we can test interactions between cyclists and drivers safely in a simulation. We will then start to look at how we can facilitate the social interaction between autonomous cars and cyclists. This will potentially involve visual displays on cars or audio feedback from them, to indicate state information to cyclists nearby (eg whether they have been detected, whether the car is letting the cyclist go ahead). We will also investigate interactions and displays for cyclists, for example multimodal displays in cycling helmets [MAT19] to give them information about car state (which could be collected by V2X software on the cyclist’s phone, for example). Or directly communicating with the car by input made on the handlebars or via gestures. These will be experimentally tested in the simulator and, if we have time, in highly controlled real driving scenarios. The output of this work will be a set new techniques to support the social interaction between autonomous vehicles and cyclists. We currently work with companies such as Jaguar Land Rover and Bosch and our results will have direct application in their products.