activity
20182024
most citedCan we enhance prosocial behavior? Using post-ride feedback to improve micromobility interactions

6 citations · 22 across the 8 of their papers we have counts for

collaborators

10 papers

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.HC20246 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.CV20224 cited

Driving Anomaly Detection Using Conditional Generative Adversarial Network

Yuning Qiu, Teruhisa Misu, Carlos Busso

Anomaly driving detection is an important problem in advanced driver assistance systems (ADAS). It is important to identify potential hazard scenarios as early as possible to avoid…

cs.HC20211 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.CV20191 cited

Grounding Human-to-Vehicle Advice for Self-driving Vehicles

Jinkyu Kim, Teruhisa Misu, Yi-Ting Chen +2

Recent success suggests that deep neural control networks are likely to be a key component of self-driving vehicles. These networks are trained on large datasets to imitate human a…

cs.LG20191 cited

Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data

Vidyasagar Sadhu, Teruhisa Misu, Dario Pompili

Corner cases are the main bottlenecks when applying Artificial Intelligence (AI) systems to safety-critical applications. An AI system should be intelligent enough to detect such s…