Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Teruhisa Misu"'
Autor:
Jacob G. Hunter, Elise Ulwelling, Matthew Konishi, Noah Michelini, Akhil Modali, Anne Mendoza, Jessie Snyder, Shashank Mehrotra, Zhaobo Zheng, Anil R. Kumar, Kumar Akash, Teruhisa Misu, Neera Jain, Tahira Reid
Publikováno v:
Frontiers in Psychology, Vol 14 (2023)
While trust in different types of automated vehicles has been a major focus for researchers and vehicle manufacturers, few studies have explored how people trust automated vehicles that are not cars, nor how their trust may transfer across different
Externí odkaz:
https://doaj.org/article/84438a87a71045888aac2041997e1e64
Autor:
Jinkyu Kim, Anna Rohrbach, Zeynep Akata, Suhong Moon, Teruhisa Misu, Yi‐Ting Chen, Trevor Darrell, John Canny
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
Abstract Humans learn to drive through both practice and theory, for example, by studying the rules, while most self‐driving systems are limited to the former. Being able to incorporate human knowledge of typical causal driving behavior should bene
Externí odkaz:
https://doaj.org/article/0b03332c2c2646a1a21cfb885107a291
Publikováno v:
IEEE Transactions on Intelligent Vehicles. 8:3154-3165
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 66:1696-1700
Augmented reality (AR) head-up display (HUD) can be a promising solution to increase drivers' situation awareness (SA) and their trust in automation. However, literature on the limitations of drivers' attention is largely lacking when it comes to des
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 66:1602-1606
In automated driving, it is important to maintain drivers’ situational awareness (SA) in order to help them avoid unnecessary interventions and negotiate challenging scenarios where human takeovers are needed. Our study developed computational mode
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 66:335-339
The objective of this study is to assess drivers’ ability to detect objects and the trajectory of these objects in scenarios with different environmental complexity levels. This is examined in the context of situation awareness (SA), defined as the
Publikováno v:
Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction.
Autor:
Matthew Konishi, Jacob G. Hunter, Zhaobo K. Zheng, Teruhisa Misu, Kumar Akash, Tahira Reid, Neera Jain
Publikováno v:
IFAC-PapersOnLine. 55:7-12
Autor:
Zhaobo Zheng, Kumar Akash, Teruhisa Misu, Vidya Krishnamoorthy, Miaomiao Dong, Yuni Lee, Gaojian Huang
Publikováno v:
INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION.
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 users take over more frequently or even disable the automation featur
Autor:
Joseph L. Gabbard, Nayara de Oliveira Faria, Kyle Tanous, Kumar Akash, Chihiro Suga, Coleman Merenda, Teruhisa Misu, Richard L. Greatbatch
Publikováno v:
Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 65:1342-1346
In the present paper, we present a user study with an advanced-driver assistance system (ADAS) using augmented reality (AR) cues to highlight pedestrians and vehicles when approaching intersections of varying complexity. Our major goal is to understa