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 Considering Human Variability in the Design of Safe Interaction with Agricultural Machinery: The Case of Foldable Roll-Over Protective Structure (FROPS) Manual Handling

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1303
Author(s):  
Margherita Micheletti Cremasco ◽  
Lucia Vigoroso ◽  
Federica Caffaro ◽  
Giuseppe Paletto ◽  
Eugenio Cavallo
Keyword(s):  
Design Solution ◽  
Protective Structure ◽  
Agricultural Machinery ◽  
Human Machine Interaction ◽  
Study Results ◽  
Manual Handling ◽  
Machine Interaction ◽  
Fatal Injuries

The foldable roll-over protective structure (FROPS) protects the operators against fatal injuries in tractor roll-over accidents. However, a rear-mounted FROPS is often folded down or removed. In the present study, the accessible zones and grasping areas in a rear-mounted FROPS were redesigned and adapted to the 5th, 50th, and 95th European human anthropometric percentiles to enhance its correct and comfortable use. Then, a rod was proposed as a design solution to make the roll-bar grasping areas fall within the new accessible zones. The rod prototype increased roll-bar reachability and facilitated the raising handling, especially for shorter users. The present study results and the accessible zones redesigned, taking into account the human percentiles, will be helpful in rethinking reachability issues in manual handling of machinery components, to support the correct behaviours, and make human-machine interaction more comfortable and safer for all.

Unsettled Issues in Vehicle Autonomy, Artificial Intelligence, and Human-Machine Interaction

2021 ◽  
Author(s):  
Chen Fang ◽  
Keyword(s):  
Artificial Intelligence ◽  
Interface Design ◽  
Autonomous Vehicles ◽  
Emotion Detection ◽  
Human Machine Interaction ◽  
Daily Lives ◽  
Current State ◽  
Speech Interaction ◽  
State Of Research ◽  
Machine Interaction

Artificial intelligence (AI)-based solutions are slowly making their way into our daily lives, integrating with our processes to enhance our lifestyles. This is major a technological component regarding the development of autonomous vehicles (AVs). However, as of today, no existing, consumer ready AV design has reached SAE Level 5 automation or fully integrates with the driver. Unsettled Issues in Vehicle Autonomy, AI and Human-Machine Interaction discusses vital issues related to AV interface design, diving into speech interaction, emotion detection and regulation, and driver trust. For each of these aspects, the report presents the current state of research and development, challenges, and solutions worth exploring.

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.

Concise CNN model for face expression recognition

2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi
Keyword(s):  
Network Architecture ◽  
Expression Recognition ◽  
Human Machine Interaction ◽  
Face Expression ◽  
Computational Overhead ◽  
Average Accuracy ◽  
Proposed Model ◽  
Face Expression Recognition ◽  
Expression Classification ◽  
Machine Interaction

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.

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.

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