activity
20182026
most citedA Classification Model for Sensing Human Trust in Machines Using EEG and GSR

163 citations · 338 across the 22 of their papers we have counts for

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Showing cs.HCShow all

17 papers · 1 filter

cs.HC2026

Adaptive Driving Style for SAE Level-2 Driving Automation: Minimizing Preference Mismatch

Kumar Akash, Zhaobo Zheng, Teruhisa Misu +4

Driving style is a key factor in the comfort and acceptance of automated vehicle (AV) features. In SAE Level-2 automation, where the driver must supervise the system and remain rea…

cs.HC2026★ 1 cited

Strategic Shaping of Human Prosociality: A Latent-State POMDP Framework

Zahra Zahedi, Xinyue Hu, Shashank Mehrotra +2

We propose a decision-theoretic framework in which a robot strategically can shape inferred human's prosocial state during repeated interactions. Modeling the human's prosociality…

cs.HC2026★ 2 cited

Exploring The Impact Of Proactive Generative AI Agent Roles In Time-Sensitive Collaborative Problem-Solving Tasks

Anirban Mukhopadhyay, Kevin Salubre, Hifza Javed +2

Collaborative problem-solving under time pressure is common but difficult, as teams must generate ideas quickly, coordinate actions, and track progress. Generative AI offers new op…

cs.HC2024

More than just a Tool: People's Perception and Acceptance of Prosocial Delivery Robots as Fellow Road Users

Vivienne Bihe Chi, Elise Ulwelling, Kevin Salubre +3

Service robots are increasingly deployed in public spaces, performing functional tasks such as making deliveries. To better integrate them into our social environment and enhance t…

cs.HC2024★ 6 cited

Can we enhance prosocial behavior? Using post-ride feedback to improve micromobility interactions

Sidney T. Scott-Sharoni, Shashank Mehrotra, Kevin Salubre +3

Micromobility devices, such as e-scooters and delivery robots, hold promise for eco-friendly and cost-effective alternatives for future urban transportation. However, their lack of…

cs.HC2024★ 2 cited

DualTake: Predicting Takeovers across Mobilities for Future Personalized Mobility Services

Zhaobo Zheng, Kumar Akash, Teruhisa Misu

A hybrid society is expected to emerge in the near future, with different mobilities interacting together, including cars, micro-mobilities, pedestrians, and robots. People may uti…

cs.HC2024

Beyond Empirical Windowing: An Attention-Based Approach for Trust Prediction in Autonomous Vehicles

Minxue Niu, Zhaobo Zheng, Kumar Akash +1

Humans' internal states play a key role in human-machine interaction, leading to the rise of human state estimation as a prominent field. Compared to swift state changes such as su…

cs.HC2023

Wellbeing in Future Mobility: Toward AV Policy Design to Increase Wellbeing through Interactions

Shashank Mehrotra, Zahra Zahedi, Teruhisa Misu +1

Recent advances in Automated vehicle (AV) technology and micromobility devices promise a transformational change in the future of mobility usage. These advances also pose challenge…

cs.HC2023★ 4 cited

Trust in Shared Automated Vehicles: Study on Two Mobility Platforms

Shashank Mehrotra, Jacob G Hunter, Matthew Konishi +6

The ever-increasing adoption of shared transportation modalities across the United States has the potential to fundamentally change the preferences and usage of different mobilitie…

cs.HC2022★ 5 cited

The Interaction Gap: A Step Toward Understanding Trust in Autonomous Vehicles Between Encounters

Jacob G. Hunter, Matthew Konishi, Neera Jain +4

Shared autonomous vehicles (SAVs) will be introduced in greater numbers over the coming decade. Due to rapid advances in shared mobility and the slower development of fully autonom…

cs.HC2022★ 10 cited

Identification of Adaptive Driving Style Preference through Implicit Inputs in SAE L2 Vehicles

Zhaobo K. Zheng, Kumar Akash, Teruhisa Misu +4

A key factor to optimal acceptance and comfort of automated vehicle features is the driving style. Mismatches between the automated and the driver preferred driving styles can make…

cs.HC2022★ 13 cited

Effects of Augmented-Reality-Based Assisting Interfaces on Drivers' Object-wise Situational Awareness in Highly Autonomous Vehicles

Xiaofeng Gao, Xingwei Wu, Samson Ho +2

Although partially autonomous driving (AD) systems are already available in production vehicles, drivers are still required to maintain a sufficient level of situational awareness…

cs.HC2021★ 1 cited

Improving Driver Situation Awareness Prediction using Human Visual Sensory and Memory Mechanism

Haibei Zhu, Teruhisa Misu, Sujitha Martin +2

Situation awareness (SA) is generally considered as the perception, understanding, and projection of objects' properties and positions. We believe if the system can sense drivers'…

cs.HC2021★ 9 cited

Clustering Human Trust Dynamics for Customized Real-time Prediction

Jundi Liu, Kumar Akash, Teruhisa Misu +1

Trust calibration is necessary to ensure appropriate user acceptance in advanced automation technologies. A significant challenge to achieve trust calibration is to quantitatively…

cs.HC2020★ 41 cited

Toward Adaptive Trust Calibration for Level 2 Driving Automation

Kumar Akash, Neera Jain, Teruhisa Misu

Properly calibrated human trust is essential for successful interaction between humans and automation. However, while human trust calibration can be improved by increased automatio…

cs.HC2020★ 73 cited

Human Trust-based Feedback Control: Dynamically varying automation transparency to optimize human-machine interactions

Kumar Akash, Griffon McMahon, Tahira Reid +1

Human trust in automation plays an essential role in interactions between humans and automation. While a lack of trust can lead to a human's disuse of automation, over-trust can re…

cs.HC2018★ 163 cited

A Classification Model for Sensing Human Trust in Machines Using EEG and GSR

Kumar Akash, Wan-Lin Hu, Neera Jain +1

Today, intelligent machines \emph{interact and collaborate} with humans in a way that demands a greater level of trust between human and machine. A first step towards building inte…