Your Interface, Your Control: Adapting Takeover Requests for Seamless Handover in Semi-Autonomous Vehicles

TL;DR

This paper presents an adaptive takeover warning system for semi-autonomous vehicles that personalizes alerts based on driver state and environment, improving safety and user experience through tailored warning strategies.

Contribution

It introduces a novel adaptive takeover warning system that personalizes alerts based on driver state and environmental context, unlike previous static warning systems.

Findings

Longer time budgets and head-up displays are effective in high-complexity environments.

Shorter time budgets and head-down displays suit hazardous events in low-complexity settings.

Personalized warning strategies enhance driver situational awareness and safety.

Abstract

With the automotive industry transitioning towards conditionally automated driving, takeover warning systems are crucial for ensuring safe collaborative driving between users and semi-automated vehicles. However, previous work has focused on static warning systems that do not accommodate different driver states. Therefore, we propose an adaptive takeover warning system that is personalised to drivers, enhancing their experience and safety. We conducted two user studies investigating semi-autonomous driving scenarios in rural and urban environments while participants performed non-driving-related tasks such as text entry and visual search. We investigated the effects of varying time budgets and head-up versus head-down displays for takeover requests on drivers' situational awareness and mental state. Through our statistical and clustering analyses, we propose strategies for designing adaptable takeover systems, e.g., using longer time budgets and head-up displays for non-hazardous takeover events in high-complexity environments while using shorter time budgets and head-down displays for hazardous events in low-complexity environments.