Abstract
In automated driving, the user interface plays an essential role in guiding transitions between automated and manual driving. This literature review identified 25 studies that explicitly studied the effectiveness of user interfaces in automated driving. Our main selection criterion was how the user interface (UI) affected take-over performance in higher automation levels allowing drivers to take their eyes off the road (SAE3 and SAE4). We categorized user interface (UI) factors from an automated vehicle-related information perspective. Short take-over times are consistently associated with take-over requests (TORs) initiated by the auditory modality with high urgency levels. On the other hand, take-over requests directly displayed on non-driving-related task devices and augmented reality do not affect take-over time. Additional explanations of take-over situation, surrounding and vehicle information while driving, and take-over guiding information were found to improve situational awareness. Hence, we conclude that advanced user interfaces can enhance the safety and acceptance of automated driving. Most studies showed positive effects of advanced UI, but a number of studies showed no significant benefits, and a few studies showed negative effects of advanced UI, which may be associated with information overload. The occurrence of positive and negative results of similar UI concepts in different studies highlights the need for systematic UI testing across driving conditions and driver characteristics. Our findings propose future UI studies of automated vehicle focusing on trust calibration and enhancing situation awareness in various scenarios.
Highlights
Cars and other road vehicles see increasing levels of support and automation
The papers addressed the following single or multiple aspects of user interfaces: ten papers studied the effect of the information channel on the take-over requests (TORs) channels via visual or auditory or tactile modality, including two papers that studied TOR on the device used by the driver in nondriving-related tasks (NDRTs); two papers investigated the benefits of an explanatory message following an abstract auditory TOR
This paper reviewed the literature for empirical studies on how user interfaces (UIs) affect take-over performance in automated vehicles
Summary
Cars and other road vehicles see increasing levels of support and automation. The majority of current and near-future automated vehicles (AVs) will still need a capable driver on-board who can take control of the vehicle when manual driving is preferred or in driving conditions that are not supported by the automation. This requires information provided by the user interface (UI) to prepare drivers and guide transitions between automated and manual driving. Level 1 automates longitudinal control (advanced cruise control) or lateral control (lane-keeping assist). Level 2 simultaneously automates longitudinal and lateral control. Drivers are always required to monitor the surroundings in
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