Zobrazeno 1 - 10
of 38 801
pro vyhledávání: '"Work A"'
Autor:
Ji, Junyi, Gloudemans, Derek, Wang, Yanbing, Zachár, Gergely, Barbour, William, Sprinkle, Jonathan, Piccoli, Benedetto, Work, Daniel B.
Analyzing stop-and-go waves at the scale of miles and hours of data is an emerging challenge in traffic research. In the past, datasets were of limited scale and could be easily analyzed by hand or with rudimentary methods to identify a very limited
Externí odkaz:
http://arxiv.org/abs/2409.00326
Autor:
Ji, Junyi, Richardson, Alex, Gloudemans, Derek, Zachár, Gergely, Nice, Matthew, Barbour, William, Sprinkle, Jonathan, Piccoli, Benedetto, Work, Daniel B.
Stop-and-go waves are a fundamental phenomenon in freeway traffic flow, contributing to inefficiencies, crashes, and emissions. Recent advancements in high-fidelity sensor technologies have improved the ability to capture detailed traffic dynamics, y
Externí odkaz:
http://arxiv.org/abs/2408.00941
Autor:
Zhang, Zhiyao, Gunter, George, Quinones-Grueiro, Marcos, Zhang, Yuhang, Barbour, William, Biswas, Gautam, Work, Daniel
This article proposes a novel approach to traffic signal control that combines phase re-service with reinforcement learning (RL). The RL agent directly determines the duration of the next phase in a pre-defined sequence. Before the RL agent's decisio
Externí odkaz:
http://arxiv.org/abs/2407.14775
Autor:
Zhang, Yuhang, Zhang, Zhiyao, Quiñones-Grueiro, Marcos, Barbour, William, Weston, Clay, Biswas, Gautam, Work, Daniel
This article presents the first field deployment of a multi-agent reinforcement-learning (MARL) based variable speed limit (VSL) control system on the I-24 freeway near Nashville, Tennessee. We describe how we train MARL agents in a traffic simulator
Externí odkaz:
http://arxiv.org/abs/2407.08021
Autor:
Coursey, Austin, Ji, Junyi, Quinones-Grueiro, Marcos, Barbour, William, Zhang, Yuhang, Derr, Tyler, Biswas, Gautam, Work, Daniel B.
Early and accurate detection of anomalous events on the freeway, such as accidents, can improve emergency response and clearance. However, existing delays and errors in event identification and reporting make it a difficult problem to solve. Current
Externí odkaz:
http://arxiv.org/abs/2406.15283
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
Let $S$ be a compact surface of genus $\geq 2$ equipped with a metric that is flat everywhere except at finitely many cone points with angles greater than $2\pi$. We examine the geodesic flow on $S$ and prove local product structure for a wide class
Externí odkaz:
http://arxiv.org/abs/2403.17791
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