Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Zeyang Cheng"'
Publikováno v:
Journal of Advanced Transportation, Vol 2022 (2022)
Traffic information and driving preference play critical roles in the route selection of drivers and further impact transport management in practice. Some studies have explored the difference between actual and shortest paths for private cars during
Externí odkaz:
https://doaj.org/article/6a80a7928762422f911180ecf1746741
Publikováno v:
Journal of Advanced Transportation, Vol 2021 (2021)
Traffic crash is a complex phenomenon that involves coupling interdependency among multiple influencing factors. Considering that interdependency is critical for predicting crash risk accurately and contributes to revealing the underlying mechanism o
Externí odkaz:
https://doaj.org/article/46fbb6041cd34ae2ba4f521b0a22e12e
A Mixed-Flow Cellular Automaton Model for Vehicle Nonstrict Priority Give-Way Behavior at Crosswalks
Publikováno v:
Journal of Advanced Transportation, Vol 2020 (2020)
The vehicle nonstrict priority give-way behavior (VNPGWB) is a common part of traffic interaction between motorized and nonmotorized vehicles in many countries. This study proposes a mixed-flow cellular automaton model to simulate the passing of vehi
Externí odkaz:
https://doaj.org/article/166132d42e5b4c46ae65dd9e4603eda3
Publikováno v:
Journal of Advanced Transportation, Vol 2019 (2019)
The speeding violation has become a key concern in the traffic safety management, as it increases the risk of traffic crashes, as well as the severity of these crashes. This uncivilized phenomenon is prominent and presents an increasing trend in Wuji
Externí odkaz:
https://doaj.org/article/3a88a93f239d44e9b4b090725463a3dd
Autor:
Wei Wang, Zeyang Cheng
Publikováno v:
Journal of Advanced Transportation, Vol 2017 (2017)
Variable Speed Limit Sign (VSLS) Systems enable speed limits to be changed dynamically in response to traffic conditions so that traffic incidents can be reduced significantly on freeway work zones. In this paper, we examined how many and where VSLS
Externí odkaz:
https://doaj.org/article/e8f2a258431d48fbbb4a9b67e7e8dbb8
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 24:4262-4276
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b4475831a9357f7e69d8c819d7cdcee
https://doi.org/10.1109/tits.2023.3234560
https://doi.org/10.1109/tits.2023.3234560
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:15329-15339
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7cfa6db755ee9591cdfc537306238e4
https://doi.org/10.1109/tits.2022.3140345
https://doi.org/10.1109/tits.2022.3140345
Publikováno v:
Nonlinear Dynamics. 109:2223-2244
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3338c955de3b82e483849e85487bbfbc
https://doi.org/10.1007/s11071-022-07436-0
https://doi.org/10.1007/s11071-022-07436-0
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:5231-5244
This study proposes a short-term traffic flow prediction framework. The vector autoregression (VAR) model based on econometric theory and the CNN-LSTM hybrid neural network model based on deep learning are employed in the analysis. An intrinsic assoc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8235e19f05b3ebb926270a4e7626cdc7
https://doi.org/10.1109/tits.2021.3052796
https://doi.org/10.1109/tits.2021.3052796
Publikováno v:
Transportmetrica A: Transport Science. :1-23
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8462ebed811b92617584ecc7f3b7752f
https://doi.org/10.1080/23249935.2022.2060368
https://doi.org/10.1080/23249935.2022.2060368