Automated driving may be a key to solving a number of problems that humanity faces today: large numbers of fatalities in traffic, traffic congestions, and increased gas emissions. However, unless the car drives itself fully automatically (such a car would not need to have a steering wheel, nor accelerator and brake pedals), the driver needs to receive information from the vehicle. Such information can be delivered by sound, visual displays, vibrotactile feedback, or a combination of two or three kinds of signals. Sound may be a particularly promising feedback modality, as sound can attract a driver’s attention irrespective of his/her momentary visual attention. Although ample research exists on warning systems and other types of auditory displays, what is less well known is how to design warning systems for automated driving specifically. Taking over control from an automated car is a spatially demanding task that may involve a high level of urgency, and warning signals (also called ‘takeover requests’, TORs) need to be designed so that the driver reacts as quickly and safely as possible. Furthermore, little knowledge is available on how to support the situation awareness and mode awareness of drivers of automated cars. The goal of this thesis is to discover how the auditory modality should be used during automated driving and to contribute towards the development of design guidelines.
|Award date||14 Dec 2018|
|Publication status||Published - 2018|