Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Srivatsan Chakravarthi Kumaran

dblp:361/3402 · DBLP profile ↗
← Back
2ranked-venue papers
2as first author
2since 2021 · last 2024
0009-0002-2528-7709ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 first-author · 2 since 2021Human-computer interaction and ubiquitous computing · 2 · 2 first-author · 2 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%
Artificial intelligence
1 paper
Autonomous driving · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
automated vehicles
0.812024
A Social Approach for Autonomous Vehicles: A Robotic Object to Enhance Passengers' Sense of Safety and Trust · HRI 2024
Human-robot interaction › nonverbal communication
nonverbal robot behavior
0.812024
A Social Approach for Autonomous Vehicles: A Robotic Object to Enhance Passengers' Sense of Safety and Trust · HRI 2024
Human-robot interaction
social robot
0.812024
A Social Approach for Autonomous Vehicles: A Robotic Object to Enhance Passengers' Sense of Safety and Trust · HRI 2024

Methods — techniques the papers use, named apart from their topics

in-situ experiment · 1.5
YearPublicationVenuePosition
2024 A Social Approach for Autonomous Vehicles: A Robotic Object to Enhance Passengers' Sense of Safety and Trust
abstract
One of the central challenges in designing autonomous vehicles concerns passenger trust and sense of safety. This challenge is related to passengers' well-established past experience with non-autonomous vehicles, which leads to concern about the absence of a driver. We explored whether it is possible to address this challenge by designing an interaction with a simple robotic object positioned on the vehicle's dashboard. The robot greeted the passenger, indicated that the vehicle was attentive to its surroundings, and informed the passenger that the drive was about to begin. We evaluated whether the robot's non-verbal behavior would provide the signals and social experience required to support passengers' trust and sense of safety. In an in-person (in-situ) experiment, participants were asked to enter an autonomous vehicle and decide if they were willing to go for a drive. As they entered the vehicle, the robot performed the designed behaviors. We evaluated the participants' considerations and experience while they made their decision. Our findings indicated that participants' trust ratings and safety-related experience were higher than those of a baseline group who did not interact with the robot. Participants also perceived the robot as providing companionship during a lonely experience. We suggest that robotic objects are a promising technology for enhancing passengers' experience in autonomous vehicles.
Srivatsan Chakravarthi Kumaran, Toam Bechor, Hadas Erel
HRI1
2023 To Cross or Not-to-Cross: A Robotic Object for Mediating Interactions Between Autonomous Vehicles and Pedestrians
abstract
A main challenge in incorporating autonomous vehicles into urban environments concerns communication with pedestrians crossing in front of them. We introduce a robotic object for facilitating natural crossing interactions by leveraging pedestrians’ existing crossing habits. The robot was designed to fit on the vehicle’s dashboard and simulate head gestures to indicate if it is safe to cross. We evaluated the perception of the robot as mediating the AV’s communication and the comprehension of its gestures, in an in-person experiment. Participants were asked to cross the road in front of a vehicle that was presented as having autonomous driving capabilities. The robot was placed on the vehicle’s dashboard in a location where pedestrians habitually look. The results indicated that when asked to cross, participants immediately looked toward the driver’s seat and easily noticed the robot. They consistently categorized the robot’s gestures into ”cross” or ”do-not-cross” categories and reported a strong sense of safety. Our findings suggest that robotic objects are a promising technology for mediating natural pedestrian-AV communication.
Srivatsan Chakravarthi Kumaran, Agam Oberlender, Andrey Grishko, Benny Megidish, Hadas Erel
RO-MAN1