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of 378
pro vyhledávání: '"Osorio, Carolina"'
Being widely adopted by the transportation and planning practitioners, the fundamental diagram (FD) is the primary tool used to relate the key macroscopic traffic variables of speed, flow, and density. We empirically analyze the relation between vehi
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A85967
https://tud.qucosa.de/api/qucosa%3A85967/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A85967/attachment/ATT-0/
Autor:
Choudhury, Shushman, Kreidieh, Abdul Rahman, Tsogsuren, Iveel, Arora, Neha, Osorio, Carolina, Bayen, Alexandre
We propose and study a data-driven framework for identifying traffic congestion functions (numerical relationships between observations of macroscopic traffic variables) at global scale and segment-level granularity. In contrast to methods that estim
Externí odkaz:
http://arxiv.org/abs/2405.06080
Autor:
Lu, Jing, Osorio, Carolina
Publikováno v:
In Transportation Research Part B July 2024 185
Autor:
Arora, Neha, Cabannes, Theophile, Ganapathy, Sanjay, Li, Yechen, McAfee, Preston, Nunkesser, Marc, Osorio, Carolina, Tomkins, Andrew, Tsogsuren, Iveel
Google Maps uses current and historical traffic trends to provide routes to drivers. In this paper, we use microscopic traffic simulation to quantify the improvements to both travel time and CO$_2$ emissions from Google Maps real-time navigation. A c
Externí odkaz:
http://arxiv.org/abs/2111.03426
Autor:
Arora, Neha, Chen, Yi-fan, Ganapathy, Sanjay, Li, Yechen, Lin, Ziheng, Osorio, Carolina, Tomkins, Andrew, Tsogsuren, Iveel
Metropolitan scale vehicular traffic modeling is used by a variety of private and public sector urban mobility stakeholders to inform the design and operations of road networks. High-resolution stochastic traffic simulators are increasingly used to d
Externí odkaz:
http://arxiv.org/abs/2109.11392
In this paper, we introduce a technique to enhance the computational efficiency of solution algorithms for high-dimensional discrete simulation-based optimization problems. The technique is based on innovative adaptive partitioning strategies that pa
Externí odkaz:
http://arxiv.org/abs/2104.14119
Autor:
Lu, Jing, Osorio, Carolina
Publikováno v:
The 101st Transportation Research Board Annual Meeting, Washington D.C., January 9-13, 2022
This paper focuses on the analytical probabilistic modeling of vehicular traffic. It formulates a stochastic node model. It then formulates a network model by coupling the node model with the link model of Lu and Osorio (2018), which is a stochastic
Externí odkaz:
http://arxiv.org/abs/2104.07129
Publikováno v:
In Transportation Research Part B December 2023 178