Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Larkin Folsom"'
Autor:
Justice Darko, Larkin Folsom, Nigel Pugh, Hyoshin Park, Khadijeh Shirzad, Justin Owens, Andrew Miller
Publikováno v:
IET Intelligent Transport Systems, Vol 16, Iss 8, Pp 1011-1025 (2022)
Abstract This research presents an adaptive and personalized routing model that enables individuals with mobility impairments to save their route preferences to a mobility assistant platform. The proactive approach based on anticipated user need acco
Externí odkaz:
https://doaj.org/article/b91e636fb1fb4fd1b47290f4be02a206
Dynamic Routing of Heterogeneous Users After Traffic Disruptions Under a Mixed Information Framework
Publikováno v:
Frontiers in Future Transportation, Vol 3 (2022)
This research focuses on reducing traffic congestion using the competing strategies between informed and uninformed drivers. Under a mixed information framework, a navigation app provides within-day route suggestions to informed drivers using predict
Externí odkaz:
https://doaj.org/article/1a9c98a9f7884064927124a35a7dda69
Publikováno v:
Earth and Space Science, Vol 9, Iss 1, Pp n/a-n/a (2022)
Abstract Lack of high‐resolution observations in the inner‐core of tropical cyclones remains a key issue when constructing an accurate initial state of the storm structure. The major implication of an improper initial state is the poor predictabi
Externí odkaz:
https://doaj.org/article/b77b4227345547b8bbb60eea5949257d
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 18 (2021)
Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different
Externí odkaz:
https://doaj.org/article/3b11e973b71945c3937633aa92e8a071
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 18 (2021)
Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different
Publikováno v:
CISS
While there has been significant progress on statistical theories in the information community, there is a lack of studies in information-theoretic distributed resource allocation to maximize information gain. With advanced technologies of unmanned a
Autor:
Hiya Roy, Hyoshin Park, Shoya Higa, Virisha Timmaraju, Jacek Sawoniewicz, Chris A. Mattmann, Kyohei Otsu, Shunichiro Nomura, Yumi Iwashita, Larkin Folsom, Gabrielle Hedrick, Sami Sahnoune, Sourish Ghosh, Olivier Lamarre, Kathryn M. Stack, Hemanth Sarabu, Shreyansh Daftry, Masahiro Ono, Sean Suehr, Brandon Rothrock, Dicong Qiu, Christopher Laporte, Annie Didier, Tanvir Islam, Vivian Z. Sun
Publikováno v:
2020 IEEE Aerospace Conference.
MAARS (Machine leaning-based Analytics for Automated Rover Systems) is an ongoing JPL effort to bring the latest self-driving technologies to Mars, Moon, and beyond. The ongoing AI revolution here on Earth is finally propagating to the red planet as
Publikováno v:
Advances in Human Factors of Transportation ISBN: 9783030205027
AHFE (13)
AHFE (13)
To better understand the effects of distracted driving on crash causation, forward roadway glance durations need to be carefully examined. Secondary tasks that impose high cognitive load lead to spillover effects that are moderated by the duration of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8771972ae3539569b3a0a9b74a965db1
https://doi.org/10.1007/978-3-030-20503-4_18
https://doi.org/10.1007/978-3-030-20503-4_18