scholarly journals Designing the Human Machine Interface to Address Range Anxiety

2012 ◽  
Vol 5 (1) ◽  
pp. 72-82 ◽  
Author(s):  
Tawhid Khan ◽  
Mark Williams ◽  
Tom Wellings ◽  
Duncan Robertson ◽  
Jackie Binersley
Keyword(s):  
Human Machine Interface ◽  
Range Anxiety ◽  
Machine Interface

scholarly journals Influence of Adaptive Human–Machine Interface on Electric-Vehicle Range-Anxiety Mitigation

2020 ◽  
Vol 4 (1) ◽  
pp. 4
Author(s):  
Antonyo Musabini ◽  
Kevin Nguyen ◽  
Romain Rouyer ◽  
Yannis Lilis
Keyword(s):  
Electric Vehicle ◽  
Autonomous Vehicle ◽  
Human Machine Interface ◽  
Traffic Light ◽  
Automated Driving ◽  
Range Anxiety ◽  
Driving Task ◽  
Machine Interface ◽  
Emergency Stop ◽  
Save Energy

The electrification of vehicles is without a doubt one of the milestones of today’s automotive technology. Even though industry actors perceive it as a future standard, acceptance, and adoption of this kind of vehicles by the end user remain a huge challenge. One of the main issues is the range anxiety related to the electric vehicle’s remaining battery level. In the scope of the H2020 ADAS&ME project, we designed and developed an intelligent Human Machine Interface (HMI) to ease acceptance of Electric Vehicle (EV) technology. This HMI is mounted on a fake autonomous vehicle piloted by a hidden joystick (called Wizard of Oz (WoZ) driving). We examined 22 inexperienced EV drivers during a one-hour driving task tailored to generate range anxiety. According to our protocol, once the remaining battery level started to become critical after manual driving, the HMI proposed accurate coping techniques to inform the drivers how to reduce the power consumption of the vehicle. In the following steps of the protocol, the vehicle was totally out of battery, and the drivers had to experience an emergency stop. The first result of this paper was that an intelligent HMI could reduce the range anxiety of the driver by proposing adapted coping strategies (i.e., transmitting how to save energy when the vehicle approaches a traffic light). The second result was that such an HMI and automated driving to a safe spot could reduce the stress of the driver when an emergency stop is necessary.

Designing the human machine interface in the ATIS domain

1990 ◽  
Author(s):  
B. Bly ◽  
P. J. Price ◽  
S. Park ◽  
S. Tepper ◽  
E. Jackson ◽  
...  
Keyword(s):  
Human Machine Interface ◽  
Machine Interface

scholarly journals Evaluation of Multimodal External Human–Machine Interface for Driverless Vehicles in Virtual Reality

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 687
Author(s):  
Jinzhen Dou ◽  
Shanguang Chen ◽  
Zhi Tang ◽  
Chang Xu ◽  
Chengqi Xue
Keyword(s):  
New Technology ◽  
Pedestrian Safety ◽  
Human Machine Interface ◽  
Visual Features ◽  
Visual Modality ◽  
Human Voice ◽  
Road Users ◽  
Machine Interface ◽  
Interaction Efficiency ◽  
Physical Features

With the development and promotion of driverless technology, researchers are focusing on designing varied types of external interfaces to induce trust in road users towards this new technology. In this paper, we investigated the effectiveness of a multimodal external human–machine interface (eHMI) for driverless vehicles in virtual environment, focusing on a two-way road scenario. Three phases of identifying, decelerating, and parking were taken into account in the driverless vehicles to pedestrian interaction process. Twelve eHMIs are proposed, which consist of three visual features (smile, arrow and none), three audible features (human voice, warning sound and none) and two physical features (yielding and not yielding). We conducted a study to gain a more efficient and safer eHMI for driverless vehicles when they interact with pedestrians. Based on study outcomes, in the case of yielding, the interaction efficiency and pedestrian safety in multimodal eHMI design was satisfactory compared to the single-modal system. The visual modality in the eHMI of driverless vehicles has the greatest impact on pedestrian safety. In addition, the “arrow” was more intuitive to identify than the “smile” in terms of visual modality.

SOLI: A Tiny Device for a New Human Machine Interface

2021 ◽  
Author(s):  
Saverio Trotta ◽  
Dave Weber ◽  
Reinhard W. Jungmaier ◽  
Ashutosh Baheti ◽  
Jaime Lien ◽  
...  
Keyword(s):  
Human Machine Interface ◽  
Machine Interface

scholarly journals Cobots in maxillofacial surgery – challenges for workplace design and the human-machine-interface

Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 488-493
Author(s):  
Florian Beuss ◽  
Frederik Schmatz ◽  
Marten Stepputat ◽  
Fabian Nokodian ◽  
Wilko Fluegge ◽  
...  
Keyword(s):  
Maxillofacial Surgery ◽  
Human Machine Interface ◽  
Workplace Design ◽  
Machine Interface

Co@N-CNT/MXene in situ grown on carbon nanotube film for multifunctional sensors and flexible supercapacitor

Nanoscale ◽  
2021 ◽  
Author(s):  
Qiufan Wang ◽  
Jiaheng Liu ◽  
Guofu Tian ◽  
Daohong Zhang
Keyword(s):  
Artificial Intelligence ◽  
Carbon Nanotube ◽  
Energy Storage ◽  
Storage Systems ◽  
Rapid Development ◽  
Human Machine Interface ◽  
Key Factors ◽  
Flexible Supercapacitor ◽  
Machine Interface

The rapid development of human-machine interface and artificial intelligence is dependent on flexible and wearable soft devices such as sensors and energy storage systems. One of the key factors for...

scholarly journals Improving Human Ground Control Performance in Unmanned Aerial Systems

2021 ◽  
Vol 13 (8) ◽  
pp. 188
Author(s):  
Marianna Di Gregorio ◽  
Marco Romano ◽  
Monica Sebillo ◽  
Giuliana Vitiello ◽  
Angela Vozella
Keyword(s):  
Situation Awareness ◽  
Interface Design ◽  
Human Machine Interface ◽  
Ground Control ◽  
Entire Group ◽  
Unmanned Aerial Systems ◽  
Ground Control Station ◽  
Machine Interface ◽  
Team Situation Awareness ◽  
Aerial Systems

The use of Unmanned Aerial Systems, commonly called drones, is growing enormously today. Applications that can benefit from the use of fleets of drones and a related human–machine interface are emerging to ensure better performance and reliability. In particular, a fleet of drones can become a valuable tool for monitoring a wide area and transmitting relevant information to the ground control station. We present a human–machine interface for a Ground Control Station used to remotely operate a fleet of drones, in a collaborative setting, by a team of multiple operators. In such a collaborative setting, a major interface design challenge has been to maximize the Team Situation Awareness, shifting the focus from the individual operator to the entire group decision-makers. We were especially interested in testing the hypothesis that shared displays may improve the team situation awareness and hence the overall performance. The experimental study we present shows that there is no difference in performance between shared and non-shared displays. However, in trials when unexpected events occurred, teams using shared displays-maintained good performance whereas in teams using non-shared displays performance reduced. In particular, in case of unexpected situations, operators are able to safely bring more drones home, maintaining a higher level of team situational awareness.

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