Natasha Merat

schoolUniversity of Leedsbar_chart#3696 Global Rank

Total Papers

HCI Rank

#3696

Research Areas

Years Active

Recent Publications

Drivers’ Attention to Dash-Based Human-Machine Interfaces: The Effect of Partial Automation and Cognitive Load

A vehicle’s dash-based Human-Machine Interface (HMI) provides critical information to drivers. However, the location of these displays can take drivers' visual attention away from the forward view and compromise safety. As vehicle automation becomes increasingly common, its impact on drivers’ visual attention to dash-…

AUTO_UI '23CorrespondingAutomated Driving Interface & Takeover Design +1

Do Drivers have Preconceived Ideas about an Automated Vehicle’s Driving Behaviour?

This study investigated drivers' preconceived notions about manoeuvres of Automated Vehicles (AVs) compared to manually driven vehicles (MVs) using a pseudo-coupled driving simulator. The simulator displayed a message indicating the state of approaching vehicles (AV/MV) in a bottleneck scenario, while participants wer…

AUTO_UI '213rd AuthorExternal HMI (eHMI) — Communication with Pedestrians & Cyclists +1

Towards future pedestrian-vehicle interactions: Introducing theoretically-supported AR prototypes

The future urban environment may consist of mixed traffic in which pedestrians interact with automated vehicles (AVs). However, it is still unclear how AVs should communicate their intentions to pedestrians. Augmented reality (AR) technology could transform the future of interactions between pedestrians and AVs by off…

AUTO_UI '19CorrespondingExternal HMI (eHMI) — Communication with Pedestrians & Cyclists

Understanding The Messages Conveyed by Automated Vehicles

Efficient and safe interactions between automated vehicles and other road users can be supported through external Human-Machine Interfaces (eHMI). The success of these interactions relies on the eHMI signals being adequately understood by other road users. A paired-comparison forced choice task (Task 1), and a 6-point…

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