Zobrazeno 1 - 10
of 4 220
pro vyhledávání: '"LEE, JONATHAN"'
Search and rescue environments exhibit challenging 3D geometry (e.g., confined spaces, rubble, and breakdown), which necessitates agile and maneuverable aerial robotic systems. Because these systems are size, weight, and power (SWaP) constrained, rap
Externí odkaz:
http://arxiv.org/abs/2411.04326
Despite their success in many domains, large language models (LLMs) remain under-studied in scenarios requiring optimal decision-making under uncertainty. This is crucial as many real-world applications, ranging from personalized recommendations to h
Externí odkaz:
http://arxiv.org/abs/2410.06238
Geological carbon sequestration (GCS) involves injecting CO$_2$ into subsurface geological formations for permanent storage. Numerical simulations could guide decisions in GCS projects by predicting CO$_2$ migration pathways and the pressure distribu
Externí odkaz:
http://arxiv.org/abs/2409.16572
In this paper, we introduce a novel geometry-aware self-training framework for room layout estimation models on unseen scenes with unlabeled data. Our approach utilizes a ray-casting formulation to aggregate multiple estimates from different viewing
Externí odkaz:
http://arxiv.org/abs/2407.15041
Autor:
Ameli, Mostafa, Mcquade, Sean, Lee, Jonathan W., Bunting, Matthew, Nice, Matthew, Wang, Han, Barbour, William, Weightman, Ryan, Denaro, Chris, Delorenzo, Ryan, Hornstein, Sharon, Davis, Jon F., Timsit, Dan, Wagner, Riley, Xu, Rita, Mahmood, Malaika, Mahmood, Mikail, Monache, Maria Laura Delle, Seibold, Benjamin, Work, Daniel B., Sprinkle, Jonathan, Piccoli, Benedetto, Bayen, Alexandre M.
Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the question of how these findings can be generalized to field operati
Externí odkaz:
http://arxiv.org/abs/2404.15533
Autor:
Seelye, Adriana, Leese, Mira Isabelle, Dorociak, Katherine, Bouranis, Nicole, Mattek, Nora, Sharma, Nicole, Beattie, Zachary, Riley, Thomas, Lee, Jonathan, Cosgrove, Kevin, Fleming, Nicole, Klinger, Jessica, Ferguson, John, Lamberty, Greg John, Kaye, Jeffrey
Publikováno v:
JMIR Formative Research, Vol 4, Iss 6, p e16371 (2020)
BackgroundAging military veterans are an important and growing population who are at an elevated risk for developing mild cognitive impairment (MCI) and Alzheimer dementia, which emerge insidiously and progress gradually. Traditional clinic-based ass
Externí odkaz:
https://doaj.org/article/fa12614f502348049c010739fce3f53f
Autor:
Jang, Kathy, Lichtlé, Nathan, Vinitsky, Eugene, Shah, Adit, Bunting, Matthew, Nice, Matthew, Piccoli, Benedetto, Seibold, Benjamin, Work, Daniel B., Monache, Maria Laura Delle, Sprinkle, Jonathan, Lee, Jonathan W., Bayen, Alexandre M.
In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and br
Externí odkaz:
http://arxiv.org/abs/2402.17050
Autor:
Lee, Jonathan W., Wang, Han, Jang, Kathy, Hayat, Amaury, Bunting, Matthew, Alanqary, Arwa, Barbour, William, Fu, Zhe, Gong, Xiaoqian, Gunter, George, Hornstein, Sharon, Kreidieh, Abdul Rahman, Lichtlé, Nathan, Nice, Matthew W., Richardson, William A., Shah, Adit, Vinitsky, Eugene, Wu, Fangyu, Xiang, Shengquan, Almatrudi, Sulaiman, Althukair, Fahd, Bhadani, Rahul, Carpio, Joy, Chekroun, Raphael, Cheng, Eric, Chiri, Maria Teresa, Chou, Fang-Chieh, Delorenzo, Ryan, Gibson, Marsalis, Gloudemans, Derek, Gollakota, Anish, Ji, Junyi, Keimer, Alexander, Khoudari, Nour, Mahmood, Malaika, Mahmood, Mikail, Matin, Hossein Nick Zinat, Mcquade, Sean, Ramadan, Rabie, Urieli, Daniel, Wang, Xia, Wang, Yanbing, Xu, Rita, Yao, Mengsha, You, Yiling, Zachár, Gergely, Zhao, Yibo, Ameli, Mostafa, Baig, Mirza Najamuddin, Bhaskaran, Sarah, Butts, Kenneth, Gowda, Manasi, Janssen, Caroline, Lee, John, Pedersen, Liam, Wagner, Riley, Zhang, Zimo, Zhou, Chang, Work, Daniel B., Seibold, Benjamin, Sprinkle, Jonathan, Piccoli, Benedetto, Monache, Maria Laura Delle, Bayen, Alexandre M.
The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. These "phantom jams" or "stop-and-go waves,"are a significant source of wasted energy. Toward this goal, the CIRC
Externí odkaz:
http://arxiv.org/abs/2402.17043
Autor:
Wang, Han, Fu, Zhe, Lee, Jonathan, Matin, Hossein Nick Zinat, Alanqary, Arwa, Urieli, Daniel, Hornstein, Sharon, Kreidieh, Abdul Rahman, Chekroun, Raphael, Barbour, William, Richardson, William A., Work, Dan, Piccoli, Benedetto, Seibold, Benjamin, Sprinkle, Jonathan, Bayen, Alexandre M., Monache, Maria Laura Delle
This paper introduces a novel control framework for Lagrangian variable speed limits in hybrid traffic flow environments utilizing automated vehicles (AVs). The framework was validated using a fleet of 100 connected automated vehicles as part of the
Externí odkaz:
http://arxiv.org/abs/2402.16993
Autor:
Chekroun, Raphael, Wang, Han, Lee, Jonathan, Toromanoff, Marin, Hornauer, Sascha, Moutarde, Fabien, Monache, Maria Laura Delle
Accurate real-time traffic state forecasting plays a pivotal role in traffic control research. In particular, the CIRCLES consortium project necessitates predictive techniques to mitigate the impact of data source delays. After the success of the Meg
Externí odkaz:
http://arxiv.org/abs/2402.05663