scholarly journals eHMI: Review and Guidelines for Deployment on Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2912
Author(s):  
Juan Carmona ◽  
Carlos Guindel ◽  
Fernando Garcia ◽  
Arturo de la Escalera
Keyword(s):  
Autonomous Vehicles ◽  
Rapid Development ◽  
Autonomous Systems ◽  
Current Status ◽  
Future Research ◽  
Human Machine Interaction ◽  
Broad Perspective ◽  
Recent Developments ◽  
Feedback Data ◽  
Machine Interaction

Human–machine interaction is an active area of research due to the rapid development of autonomous systems and the need for communication. This review provides further insight into the specific issue of the information flow between pedestrians and automated vehicles by evaluating recent advances in external human–machine interfaces (eHMI), which enable the transmission of state and intent information from the vehicle to the rest of the traffic participants. Recent developments will be explored and studies analyzing their effectiveness based on pedestrian feedback data will be presented and contextualized. As a result, we aim to draw a broad perspective on the current status and recent techniques for eHMI and some guidelines that will encourage future research and development of these systems.

scholarly journals A Bibliometric Analysis of Human-Machine Interaction Methodology for Electric-Powered Wheelchairs Driving from 1998 to 2020

2021 ◽  
Vol 18 (14) ◽  
pp. 7567
Author(s):  
Xiaochen Zhang ◽  
Lanxin Hui ◽  
Linchao Wei ◽  
Fuchuan Song ◽  
Fei Hu
Keyword(s):  
The Elderly ◽  
Research Field ◽  
Future Research ◽  
Human Machine Interaction ◽  
Research Directions ◽  
The Past ◽  
Power Wheelchairs ◽  
The Disabled ◽  
Future Research Directions ◽  
Machine Interaction

Electric power wheelchairs (EPWs) enhance the mobility capability of the elderly and the disabled, while the human-machine interaction (HMI) determines how well the human intention will be precisely delivered and how human-machine system cooperation will be efficiently conducted. A bibliometric quantitative analysis of 1154 publications related to this research field, published between 1998 and 2020, was conducted. We identified the development status, contributors, hot topics, and potential future research directions of this field. We believe that the combination of intelligence and humanization of an EPW HMI system based on human-machine collaboration is an emerging trend in EPW HMI methodology research. Particular attention should be paid to evaluating the applicability and benefits of the EPW HMI methodology for the users, as well as how much it contributes to society. This study offers researchers a comprehensive understanding of EPW HMI studies in the past 22 years and latest trends from the evolutionary footprints and forward-thinking insights regarding future research.

scholarly journals Non-invasive imaging of the coronary arteries

2018 ◽  
Vol 40 (29) ◽  
pp. 2444-2454 ◽  
Author(s):  
Philip D Adamson ◽  
David E Newby
Keyword(s):  
Coronary Arteries ◽  
Randomized Clinical Trials ◽  
Rapid Development ◽  
Current Status ◽  
Future Research ◽  
Research Perspective ◽  
Non Invasive ◽  
Positron Emission ◽  
Prognostic Stratification

Abstract Non-invasive imaging of the coronary arteries is an enterprise in rapid development. From the research perspective, there is great demand for in vivo techniques that can reliably identify features of high-risk plaque that may offer insight into pathophysiological processes and act as surrogate indicators of response to therapeutic intervention. Meanwhile, there is clear clinical need for greater accuracy in diagnosis and prognostic stratification. Fortunately, ongoing technological improvements and emerging data from randomized clinical trials are helping make these elusive goals a reality. This review provides an update on the current status of non-invasive coronary imaging with computed tomography, magnetic resonance, and positron emission tomography with a focus on current clinical applications and future research directions.

Neuronal signaling in schistosomes: current status and prospects for postgenomicsThe present review is one of a series of occasional review articles that have been invited by the Editors and will feature the broad range of disciplines and expertise represented in our Editorial Advisory Board.

2010 ◽  
Vol 88 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Paula Ribeiro ◽  
Timothy G. Geary
Keyword(s):  
Molecular Mechanisms ◽  
Current Status ◽  
Future Research ◽  
Neuronal Signaling ◽  
Neuronal Communication ◽  
Therapeutic Drugs ◽  
Rich Diversity ◽  
Recent Developments ◽  
Transmitter Receptors ◽  
Etiological Agents

Parasitic platyhelminths of the genus Schistosoma Weinland, 1858 (Trematoda, Digenea) are the etiological agents of human schistosomiasis, one of the most prevalent and debilitating parasitic diseases worldwide. Praziquantel is the only drug treatment available in most parts of the world and the effectiveness of the drug is threatened by the prospect of drug resistance. There is a pressing need to learn more about the basic biology of this organism and to identify molecular targets for new therapeutic drugs. The nervous system of schistosomes coordinates many activities that are essential for parasite survival, and as such is an attractive target for chemotherapeutic intervention. Until recently, very little was known about the molecular mechanisms of neuronal signaling in these organisms, but this is rapidly changing following the completion of the genome sequence and several recent developments in schistosome transgenesis and gene silencing. Here we review the current status of schistosome neurobiology and discuss prospects for future research as the field moves into a postgenomics era. One of the themes that will emerge from this discussion is that schistosomes have a rich diversity of neurotransmitters and receptors, indicating a more sophisticated system of neuronal communication than might be expected of a parasitic flatworm. Moreover, many of these transmitter receptors share little sequence homology with those of the human host, making them ideally suited for selective drug targeting. Strategies for characterization of these important parasite proteins will be discussed.

scholarly journals Soft Actuators and  Robotic Devices for Rehabilitation and Assistance           

2021 ◽  
Author(s):  
Min Pan ◽  
Chenggang Yuan ◽  
Xianrong Liang ◽  
Tianyun Dong ◽  
Tao Liu ◽  
...  
Keyword(s):  
Piezoelectric Materials ◽  
Control Strategies ◽  
Assistive Devices ◽  
Future Research ◽  
Human Machine Interaction ◽  
New Device ◽  
Liquid Crystal Elastomers ◽  
Robotic Devices ◽  
Soft Actuators ◽  
Machine Interaction

Soft actuators and robotic devices have been increasingly applied to the field of rehabilitation and assistance, where safe human and machine interaction is of particular importance. Compared with their widely used rigid counterparts, soft actuators and robotic devices can provide a range of significant advantages; these include safe interaction, a range of complex motions, ease of fabrication and resilience to a variety of environments. In recent decades, significant effort has been invested in the development of soft rehabilitation and assistive devices for improving a range of medical treatments and quality of life. This review provides an overview of the current state-of-the-art in soft actuators and robotic devices for rehabilitation and assistance, in particular systems that achieve actuation by pneumatic and hydraulic fluid-power, electrical motors, chemical reactions and soft active materials such as dielectric elastomers, shape memory alloys, magnetoactive elastomers, liquid crystal elastomers and piezoelectric materials. Current research on soft rehabilitation and assistive devices is in its infancy, and new device designs and control strategies for improved performance and safe human-machine interaction are identified as particularly untapped areas of research. Finally, insights into future research directions are outlined. Corresponding author(s) Email:   [email protected], [email protected]

scholarly journals A Conceptual Framework for Machine Self-Presentation and Trust

2021 ◽  
Vol 2 (1) ◽  
pp. 20-45
Author(s):  
Jeff Stanley ◽  
Ozgur Eris ◽  
Monika Lohani
Keyword(s):  
Literature Review ◽  
Research And Development ◽  
Conceptual Framework ◽  
Human Interaction ◽  
Future Research ◽  
Human Machine Interaction ◽  
Self Presentation ◽  
Verbal Behaviors ◽  
Psychosocial Model ◽  
Machine Interaction

Increasingly, researchers are creating machines with humanlike social behaviors to elicit desired human responses such as trust and engagement, but a systematic characterization and categorization of such behaviors and their demonstrated effects is missing. This paper proposes a taxonomy of machine behavior based on what has been experimented with and documented in the literature to date. We argue that self-presentation theory, a psychosocial model of human interaction, provides a principled framework to structure existing knowledge in this domain and guide future research and development. We leverage a foundational human self-presentation taxonomy (Jones and Pittman, 1982), which associates human verbal behaviors with strategies, to guide the literature review of human-machine interaction studies we present in this paper. In our review, we identified 36 studies that have examined human-machine interactions with behaviors corresponding to strategies from the taxonomy. We analyzed frequently and infrequently used strategies to identify patterns and gaps, which led to the adaptation of Jones and Pittman’s human self-presentation taxonomy to a machine self-presentation taxonomy. The adapted taxonomy identifies strategies and behaviors machines can employ when presenting themselves to humans in order to elicit desired human responses and attitudes. Drawing from models of human trust we discuss how to apply the taxonomy to affect perceived machine trustworthiness.

scholarly journals Turn-Taking and Coordination in Human-Machine Interaction

AI Magazine ◽  
2017 ◽  
Vol 37 (4) ◽  
pp. 5-6 ◽  
Author(s):  
Sean Andrist ◽  
Dan Bohus ◽  
Bilge Mutlu ◽  
David Schlangen
Keyword(s):  
Autonomous Systems ◽  
Research Area ◽  
Human Robot Interaction ◽  
Research Progress ◽  
Virtual Agents ◽  
Human Machine Interaction ◽  
Dialog Systems ◽  
Turn Taking ◽  
Core Concepts ◽  
Machine Interaction

This issue of AI Magazine brings together a collection of articles on challenges, mechanisms, and research progress in turn-taking and coordination between humans and machines. The contributing authors work in interrelated fields of spoken dialog systems, intelligent virtual agents, human-computer interaction, human-robot interaction, and semiautonomous collaborative systems and explore core concepts in coordinating speech and actions with virtual agents, robots, and other autonomous systems. Several of the contributors participated in the AAAI Spring Symposium on Turn-Taking and Coordination in Human-Machine Interaction, held in March 2015, and several articles in this issue are extensions of work presented at that symposium. The articles in the collection address key modeling, methodological, and computational challenges in achieving effective coordination with machines, propose solutions that overcome these challenges under sensory, cognitive, and resource restrictions, and illustrate how such solutions can facilitate coordination across diverse and challenging domains. The contributions highlight turn-taking and coordination in human-machine interaction as an emerging and evolving research area with important implications for future applications of AI.

Fungicide resistance in Venturia effusa, cause of pecan scab: current status and practical implications

2020 ◽  
Author(s):  
Jeff Standish ◽  
Tim Brenneman ◽  
Clive Bock ◽  
Katherine Stevenson
Keyword(s):  
Fungicide Resistance ◽  
Operating Cost ◽  
Resistance Management ◽  
Research Priorities ◽  
Current Status ◽  
Future Research ◽  
Pecan Scab ◽  
Recent Developments ◽  
Benzimidazole Carbamates ◽  
Practical Implications

Pecan scab, caused by Venturia effusa, is the most economically damaging disease of pecan in the southeastern U.S. and annual epidemics are most effectively managed through multiple fungicide applications. The fungicide applications can be the single greatest operating cost for commercial growers and the return on that investment is impacted by fungicide resistance. Venturia effusa produces multiple generations of conidia per season, exhibits substantial genetic diversity, overwinters as stromata in the tree, and is under immense selection from the applied fungicides, all of which lead to a high risk for developing fungicide resistance. Since the mid-1970s, resistance or reduced sensitivity has been observed in isolates of V. effusa to the methyl benzimidazole carbamates, demethylation inhibitors, quinone outside inhibitors, organotin compounds and the guanidines. Over the last ten years, several studies have been conducted that have improved both scab management and fungicide resistance management in V. effusa. The aim of this review is to summarize recent developments in our understanding of fungicide resistance in V. effusa in the context of scab management in southeastern pecan orchards. The history, modes of action, general use of the labelled fungicides, and mechanisms and stability of fungicide resistance in V. effusa are discussed; conclusions and future research priorities are also presented.

scholarly journals DESIGNING FOR CALIBRATED TRUST: EXPLORING THE CHALLENGES IN CALIBRATING TRUST BETWEEN USERS AND AUTONOMOUS VEHICLES

2021 ◽  
Vol 1 ◽  
pp. 1143-1152
Author(s):  
David Callisto Valentine ◽  
Iskander Smit ◽  
Euiyoung Kim
Keyword(s):  
Thematic Analysis ◽  
Autonomous Vehicles ◽  
Design Solution ◽  
Complex Nature ◽  
Sweet Spot ◽  
Human Machine Interaction ◽  
Use Phase ◽  
Clear Communication ◽  
Machine Interaction

AbstractTrust is an important factor in building acceptance of autonomous vehicles within our society, but the complex nature of trust makes it challenging to design for an appropriate level of trust. This can lead to instances of mistrust and/or distrust between users and AV’s. Designing for calibrated trust is a possible option to address this challenge. Existing research on designing for calibrated trust focuses on the human machine interaction (HMI), while from literature we infer that trust creation beings much before the first interaction between a user and an AV. The goal of our research is to broaden the scope of calibrated trust, by exploring the pre-use phase and understand the challenges faced in calibration of trust. Within our study 16 mobility experts were interviewed and a thematic analysis of the interviews was conducted. The analysis revealed the lack of clear communication between stakeholders, a solutionism approach towards designing and lack of transparency in design as the prominent challenges. Building on the research insights, we briefly introduce the Calibrated Trust Toolkit as our design solution, and conclude by proposing a sweet spot for achieving calibration of trust between users and autonomous vehicles.

scholarly journals From Interaction to Cooperation: a new approach for human-machine interaction research for closing the out-of-the-loop unfamiliarity

2020 ◽  
Author(s):  
Maximilian Alexander Wächter ◽  
Farbod Nosrat Nezami. ◽  
Nora Maleki ◽  
Philipp Spaniol ◽  
Lea Maria Kühne ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Future Research ◽  
Close Monitoring ◽  
Visual Aids ◽  
Human Machine Interaction ◽  
Out Of The Loop ◽  
Human Driver ◽  
Access Cost ◽  
Cost Efficient ◽  
Cooperation Partners

With the introduction of autonomous vehicles, drivers will be able to engage in non-related tasks while being driven. But in critical situations the car needs the support of the human driver. How do distracted drivers get back into the control-loop quickly when the car requests a take-over? To investigate effective take-over actions, we developed an interactive virtual reality experiment, that uses premises of the embodied cognition theory. Accordingly, the car should not only provide sensory input, but also help enhance the driver’s motor response by interpreting intention and thus helping to accomplish desired actions. This binds humans and machines together in becoming true cooperation partners in joint action. Therefore, we aim for a close monitoring of participants combined with sensorimotor feedforward and feedback. The presented prototype also serves as an open-access, cost-efficient toolkit that enables interested researchers to tailor the presented LoopAR tool to their own needs as part of a previously published toolkit called WestDrive. With the presented work, we hope to shift the paradigm of future research from only visual aids to full sensorimotor integration assistance.

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