Lee Skrypchuk

TL;DR: This work analyses the data from these disengagement reports with the aim of gainingetter understanding of the situations in which a driver is required to takeover, as this is potentially useful in improving the Society of Automotive Engineers Level 2 and Level 3 automation technologies.

TL;DR: Investigating the effects of visual and haptic touchscreen feedback on visual workload, task performance and subjective response using a medium-fidelity driving simulator showed that visual workload was increased when visual feedback was delayed or absent; however, introducing haptic feedback counteracted this effect.

TL;DR: A dynamic model of drivers’ neuromuscular interaction with a steering wheel is first established and key parameters of the transfer function model are identified by using the Gauss–Newton algorithm.

TL;DR: In this article, the authors present a display method for use in vehicle, comprising obtaining information associated with a vehicle or image data for a region ahead of the vehicle, and displaying one or more of a graphical representation of at least one component of a vehicle.

TL;DR: A qualitative, Wizard-of-Oz study to explore how drivers might interact linguistically with a natural language digital driving assistant and can be used to inform the design of future in-vehicle natural language systems.