Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Muhammad Tayyab Asif"'
Autor:
Patrick Jaillet, Muhammad Tayyab Asif, Anatolii Prokhorchuk, Aleksandar Stevanovic, Usman Muhammad, Justin Dauwels, Nikola Mitrovic
Accurate prediction of network-level traffic parameters during inclement weather conditions can greatly help in many transportation applications. Rainfall tends to have a quantifiable impact on driving behavior and traffic network performance. This i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32e2b175b620b0ea5f96e519ec5b507b
https://hdl.handle.net/10356/161883
https://hdl.handle.net/10356/161883
Autor:
Muhammad Tayyab Asif
Developing models for large road networks is not a trivial task. We propose data driven models that can help intelligent transportation systems (ITS) in dealing with issues such as managing large amount of traffic information and incomplete data sets
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::774f1c6e895402265f898036aa461909
https://doi.org/10.32657/10356/65985
https://doi.org/10.32657/10356/65985
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 17:1816-1825
Intelligent transportation systems (ITSs) gather information about traffic conditions by collecting data from a wide range of on-ground sensors. The collected data usually suffer from irregular spatial and temporal resolution. Consequently, missing d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9d78cfcd1a1e3760b7f1495af7f23cec
https://doi.org/10.1109/tits.2015.2507259
https://doi.org/10.1109/tits.2015.2507259
Autor:
Muhammad Tayyab Asif, Nikola Mitrovic, Aditya Narayanan, Ansar Rauf, Justin Dauwels, Patrick Jaillet
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 17:1988-1997
The role of smartphones in traffic applications is typically limited to front-end interface. Although smartphones have significant computational resources, which are most likely to increase further in the near future, most of the computations are sti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fd092b08619b71cb0c03e9981ac315d
https://doi.org/10.1109/tits.2016.2519922
https://doi.org/10.1109/tits.2016.2519922
Publikováno v:
MIT web domain
With advancements in sensor technologies, intelligent transportation systems can collect traffic data with high spatial and temporal resolution. However, the size of the networks combined with the huge volume of the data puts serious constraints on s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a080d53e1816b23b67b4f0b21dc0dcc0
https://doi.org/10.1109/tits.2014.2374335
https://doi.org/10.1109/tits.2014.2374335
Publikováno v:
CDC
We propose a new method for traffic state estimation applicable to large urban road networks where a significant amount of the real-time and historical data is missing. Our proposed approach involves estimating the missing historical data through low
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e09b5ed324e47b8ea1b908e93378a5ed
https://doi.org/10.1109/cdc.2017.8264610
https://doi.org/10.1109/cdc.2017.8264610
Autor:
Ali Oran, Justin Dauwels, Chong Yang Goh, Muye Xu, Muhammad Tayyab Asif, Esmail Fathi, Nikola Mitrovic, Patrick Jaillet, Menoth Mohan Dhanya
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 15:794-804
The ability to accurately predict traffic speed in a large and heterogeneous road network has many useful applications, such as route guidance and congestion avoidance. In principle, data-driven methods, such as support vector regression (SVR), can p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2117c826519e22ea4761b7dea590d86
https://doi.org/10.1109/tits.2013.2290285
https://doi.org/10.1109/tits.2013.2290285
Publikováno v:
2016 IEEE Region 10 Conference (TENCON).
Traffic incidents such as accidents or vehicle breakdowns are one of the major causes of traffic congestion in urban areas. Consequently, accurate prediction of duration of these incidents is considered as one of the most important challenges by traf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59caa3b36155f4003da305b78ff91509
https://doi.org/10.1109/tencon.2016.7847964
https://doi.org/10.1109/tencon.2016.7847964
Autor:
Justin Dauwels, Wentong Cai, Ulrich Fastenrath, Banishree Ghosh, Muhammad Tayyab Asif, Hongliang Guo
Publikováno v:
ITSC
In metropolitan areas, about 50% of traffic delays are caused by non-recurring traffic incidents. Hence, accurate prediction of the duration of such events is critical for traffic management authorities. In this paper, we study the predictability of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33ff9043e835953f9989886a76222474
http://hdl.handle.net/10220/42471
http://hdl.handle.net/10220/42471
Autor:
Chetan Belagal Math, Justin Dauwels, Muhammad Tayyab Asif, Nikola Mitrovic, Apratim Choudhury, Hong Li, Tomasz Maszczyk
Publikováno v:
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016, 1017-1022
STARTPAGE=1017;ENDPAGE=1022;TITLE=2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016
ITSC
STARTPAGE=1017;ENDPAGE=1022;TITLE=2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016
ITSC
One of the most exciting applications of V2X technologies, that is envisioned, is the platooning of a series of autonomous vehicles led by a manually driven vehicle. However, the realization of this application depends entirely on the efficacy of a p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d73419067f21022d6ea47cc9c6e91e49
https://doi.org/10.1109/ITSC.2016.7795680
https://doi.org/10.1109/ITSC.2016.7795680