Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Gao, Jingqin"'
While deep learning has shown success in predicting traffic states, most methods treat it as a general prediction task without considering transportation aspects. Recently, graph neural networks have proven effective for this task, but few incorporat
Externí odkaz:
http://arxiv.org/abs/2406.13057
Although traffic prediction has been receiving considerable attention with a number of successes in the context of intelligent transportation systems, the prediction of traffic states over a complex transportation network that contains different road
Externí odkaz:
http://arxiv.org/abs/2406.13038
The rapid growth in terms of the availability of transportation data provides great potential for the introduction of emerging data-driven methodologies into transportation-related research and development efforts. However, advanced data-driven model
Externí odkaz:
http://arxiv.org/abs/2406.15452
Publikováno v:
In Transportation Research Interdisciplinary Perspectives July 2024 26
Double parking that often negatively affects traffic operations and safety is not a new phenomenon on urban streets. This study proposes a novel data-driven integrated framework for estimating the actual frequency of double parking so that both micro
Externí odkaz:
http://arxiv.org/abs/2011.11238
Autor:
Gao, Jingqin, Wang, Jingxing, Bian, Zilin, Bernardes, Suzana Duran, Chen, Yanyan, Bhattacharyya, Abhinav, Thambiran, Siva Soorya Muruga, Ozbay, Kaan, Iyer, Shri, Xuegang, Ban
This paper continues to highlight trends in mobility and sociability in New York City (NYC), and supplements them with similar data from Seattle, WA, two of the cities most affected by COVID-19 in the U.S. Seattle may be further along in its recovery
Externí odkaz:
http://arxiv.org/abs/2010.01170
The novel Coronavirus COVID-19 spreading rapidly throughout the world was recognized by the World Health Organization (WHO) as a pandemic on March 11, 2020. One month into the COVID-19 pandemic, this white paper looks at the initial impacts COVID-19
Externí odkaz:
http://arxiv.org/abs/2010.01168
Autor:
Wang, Ding, Zuo, Fan, Gao, Jingqin, He, Yueshuai, Bian, Zilin, Bernardes, Suzana Duran, Na, Chaekuk, Wang, Jingxing, Petinos, John, Ozbay, Kaan, Chow, Joseph Y. J., Iyer, Shri, Nassif, Hani, Ban, Xuegang Jeff
The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped by social distancing. This edition of the white paper updates travel
Externí odkaz:
http://arxiv.org/abs/2010.09648
Autor:
Bernardes, Suzana Duran, Bian, Zilin, Thambiran, Siva Sooryaa Muruga, Gao, Jingqin, Na, Chaekuk, Zuo, Fan, Hudanich, Nick, Bhattacharyya, Abhinav, Ozbay, Kaan, Iyer, Shri, Chow, Joseph Y. J., Nassif, Hani
New York City (NYC) is entering Phase 4 of the state's reopening plan, starting July 20, 2020. This white paper updates travel trends observed during the first three reopening phases and highlights the spatial distributions in terms of bus speeds and
Externí odkaz:
http://arxiv.org/abs/2009.14019
Autor:
Gao, Jingqin, Bhattacharyya, Abhinav, Wang, Ding, Hudanich, Nick, Sooryaa, Siva, Thambiran, Muruga, Bernardes, Suzana Duran, Na, Chaekuk, Zuo, Fan, Bian, Zilin, Ozbay, Kaan, Iyer, Shri, Nassif, Hani, Chow, Joseph Y. J.
Six months into the pandemic and one month after the phase four reopening in New York City (NYC), restrictions are lifting, businesses and schools are reopening, but global infections are still rising. This white paper updates travel trends observed
Externí odkaz:
http://arxiv.org/abs/2009.14018