Zobrazeno 1 - 10
of 306
pro vyhledávání: '"J Khattak"'
Autor:
Kouhyar Sheida, Mohammad Seyedi, Muhammad Ali Afridi, Farzad Ferdowsi, Mohammad J. Khattak, Vijaya K. Gopu, Tyson Rupnow
Publikováno v:
Machines, Vol 12, Iss 10, p 694 (2024)
This research study presents a resilient control scheme for an islanded DC microgrid (DC MG) integrating solar photovoltaic (PV), battery storage (BESS), and piezoelectric (PE) energy harvesting modules. The microgrid (MG) case study represents an en
Externí odkaz:
https://doaj.org/article/b5ebd00632eb44c1b18336caa131c728
Publikováno v:
Transportation Research Interdisciplinary Perspectives, Vol 24, Iss , Pp 101073- (2024)
This study employs a unique methodology for analyzing seasonal traffic crashes by first identifying adverse winter-weather events using traditional traffic-crash data (from Nebraska) and correlating them to detailed meteorological data for subsequent
Externí odkaz:
https://doaj.org/article/7726f53772a446e988dc9efebad513ff
Publikováno v:
Journal of Advanced Transportation, Vol 2024 (2024)
The connected and automated car-following model can provide a model reference for the queue control algorithm of connected and automated driving and has become a hot research topic in the field of connected vehicles and intelligent transportation. A
Externí odkaz:
https://doaj.org/article/9a97311cf5ac4d858a4862da08272390
Autor:
Muhammad Umer Farooq, Aemal J. Khattak
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11537 (2023)
The highway–rail grade crossings (HRGCs) crash frequency models used in the US are based on the Federal Railroad Administration’s (FRA) database for highway–rail crossing inventory. Inaccuracies or missing values within this database directly i
Externí odkaz:
https://doaj.org/article/83b8819c6a604896a02e7187453d4431
Publikováno v:
IET Intelligent Transport Systems, Vol 14, Iss 5, Pp 306-312 (2020)
Abnormal driving behaviours, such as rapid acceleration, emergency braking, and rapid lane changing, bring great uncertainty to traffic, and can easily lead to traffic accidents. The accurate identification of abnormal driving behaviour helps to judg
Externí odkaz:
https://doaj.org/article/0498d7b1282a437989145956b406b482
Publikováno v:
Applied Sciences, Vol 12, Iss 9, p 4678 (2022)
In developing countries, heavy-duty trucks play an important role in transportation for infrastructure construction. However, frequent truck accidents cause great losses. Previous studies have mainly focused on passenger drivers; to date, little has
Externí odkaz:
https://doaj.org/article/0ecfe2be623147c0a9467ccb9594ef35
Publikováno v:
Journal of Advanced Transportation, Vol 2021 (2021)
A correct lane-changing plays a crucial role in traffic safety. Predicting the lane-changing behavior of a driver can improve the driving safety significantly. In this paper, a hybrid neural network prediction model based on recurrent neural network
Externí odkaz:
https://doaj.org/article/b8366c9bf7e04562bb178265a2389b1e
Publikováno v:
Digital Transportation and Safety. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd4302de3f7263f5f181ec501e13574f
https://doi.org/10.48130/dts-2023-0009
https://doi.org/10.48130/dts-2023-0009
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 23:24248-24262
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db94ac89933742a131e0fb705b666342
https://doi.org/10.1109/tits.2022.3204033
https://doi.org/10.1109/tits.2022.3204033
Publikováno v:
Journal of Advanced Transportation, Vol 2020 (2020)
The existing model of sudden acceleration changes, referred to as the traffic jerk effect, is mostly based on theoretical hypotheses, and previous research has mainly focused on traditional traffic flow. To this end, this paper investigates the chang
Externí odkaz:
https://doaj.org/article/c87113a0bf094378bcb70c4d6e8e9232