Zobrazeno 1 - 10
of 145
pro vyhledávání: '"Junfeng Jiao"'
Publikováno v:
PLoS ONE, Vol 19, Iss 9, p e0309302 (2024)
The deployment of public electric vehicle charging stations (EVCS) is a critical component of transportation electrification. Recent studies have highlighted growing concerns about disparities in accessibility to public chargers between different dem
Externí odkaz:
https://doaj.org/article/8db21218f82647518d8d7708102f13ee
Autor:
Seung Jun Choi, Junfeng Jiao
Publikováno v:
PLoS ONE, Vol 19, Iss 7, p e0306782 (2024)
Transit deserts refer to regions with a gap in transit services, with the demand for transit exceeding the supply. This study goes beyond merely identifying transit deserts to suggest actionable solutions. Using a multi-class supervised machine learn
Externí odkaz:
https://doaj.org/article/7c9158543a0347f5ae6eed495b5cb071
Autor:
Manmeet Singh, Nachiketa Acharya, Sajad Jamshidi, Junfeng Jiao, Zong-Liang Yang, Marc Coudert, Zach Baumer, Dev Niyogi
Publikováno v:
Computational Urban Science, Vol 3, Iss 1, Pp 1-13 (2023)
Abstract Cities need climate information to develop resilient infrastructure and for adaptation decisions. The information desired is at the order of magnitudes finer scales relative to what is typically available from climate analysis and future pro
Externí odkaz:
https://doaj.org/article/df3a053a26c04eb5bca1d77fc5b7c47d
Autor:
Seung Jun Choi, Junfeng Jiao
Publikováno v:
Applied Sciences, Vol 14, Iss 5, p 1826 (2024)
This study explores the socioeconomic disparities observed in the early adoption of Electric Vehicles (EVs) in the United States. A multiagent deep reinforcement learning-based policy simulator was developed to address the disparities. The model, tes
Externí odkaz:
https://doaj.org/article/2e79264231844c56863b9bbdf501a123
Publikováno v:
Computational Urban Science, Vol 1, Iss 1, Pp 1-16 (2021)
Abstract Although studies have previously investigated the spatial factors of COVID-19, most of them were conducted at a low resolution and chose to limit their study areas to high-density urbanized regions. Hence, this study aims to investigate the
Externí odkaz:
https://doaj.org/article/4fd9d93144984b9a8dd61d1441835f7c
Publikováno v:
Land, Vol 12, Iss 2, p 358 (2023)
Transit-oriented development has been a widely accepted tool among transportation planning practitioners; however, there are concerns about the risk of increasing residential property values leading to gentrification or displacements. Therefore, it i
Externí odkaz:
https://doaj.org/article/93fecb47457a48179a263837a8b4bb87
Autor:
Amin Azimian, Junfeng Jiao
Publikováno v:
Findings (2021)
In this study, we utilized a random forest model to predict the "L" train’s daily ridership in the Chicago downtown area during the pandemic based on environmental, transportation, and COVID-19-related factors. The results indicated that the model
Externí odkaz:
https://doaj.org/article/99d1eb6087c548d9bbd655c9dbd11045
Autor:
Junfeng Jiao, Amin Azimian
Publikováno v:
Findings (2021)
The COVID-19 outbreak posed a considerable risk to the health of people in the US and across the world. To reduce its spread, various companies in America adopted a range of preventive measures, such as telework, for the majority of their workforces.
Externí odkaz:
https://doaj.org/article/4a8a4919d7fa49538cd997f7de02ec13
Publikováno v:
Journal of Transport and Land Use, Vol 13, Iss 1 (2020)
Land-use patterns and rapid urban sprawl greatly influence older adults’ mobility in China. Older pedestrians’ safety issues are crucial because these people are more frequently injured in traffic accidents. This research aims to investigate what
Externí odkaz:
https://doaj.org/article/96cf4e911df74ebb896c3bf61394e4af
Publikováno v:
Journal of Transport and Land Use, Vol 13, Iss 1 (2020)
We planned this special issue in response to the new opportunities and innovations for urban transport planning in China all of which can help build the smart transportation systems of the future. In preparation for the special issue, we organized th
Externí odkaz:
https://doaj.org/article/d654ef6eee0a41c2aa26745703cdbc4c