Zobrazeno 1 - 10
of 242
pro vyhledávání: '"Javier, Gozalvez"'
Autor:
Jesus Mena-Oreja, Javier Gozalvez
Publikováno v:
IEEE Access, Vol 9, Pp 133710-133724 (2021)
Traffic prediction helps mitigate the impact of traffic congestion. The accuracy of traffic predictions depends on the availability of the data used for the prediction as well as the prediction model. Data from fixed traffic detectors is only availab
Externí odkaz:
https://doaj.org/article/d27ac6e308124dde96092fe0ea7f20bf
Autor:
Juan Jesus Gonzalez-Delicado, Javier Gozalvez, Jesus Mena-Oreja, Miguel Sepulcre, Baldomero Coll-Perales
Publikováno v:
IEEE Access, Vol 9, Pp 154423-154434 (2021)
The design, testing and optimization of Vehicle to Everything (V2X), connected and automated driving and Intelligent Transportation Systems (ITS) and technologies requires mobility traces and traffic simulation scenarios that can faithfully character
Externí odkaz:
https://doaj.org/article/8ffa382dcf22473e894114674b6c6076
Publikováno v:
IEEE Access, Vol 8, Pp 121526-121548 (2020)
V2X (Vehicle to everything) communications can be currently supported by standards based on IEEE 802.11p (e.g. DSRC or ITS-G5) or LTE-V2X (also known as Cellular V2X or C-V2X) technologies. There has been an intense debate in the community on which t
Externí odkaz:
https://doaj.org/article/a01e912df52f470984eecdd7d4599708
Autor:
Jesus Mena-Oreja, Javier Gozalvez
Publikováno v:
IEEE Access, Vol 8, Pp 91188-91212 (2020)
Deep learning-based techniques are the state of the art in road traffic prediction or forecasting. Several deep neural networks have been proposed to predict the traffic but they have not been evaluated under common datasets. Current studies analyze
Externí odkaz:
https://doaj.org/article/8434d3cbcc3c423d97cc936d4c8274a4
Autor:
Miguel Sepulcre, Javier Gozalvez, Gokulnath Thandavarayan, Baldomero Coll-Perales, Julian Schindler, Michele Rondinone
Publikováno v:
IEEE Access, Vol 8, Pp 214254-214268 (2020)
The emergence of connected automated vehicles and advanced V2X applications and services can challenge the scalability of vehicular networks in the future. This challenge requires solutions to reduce and control the communication channel load beyond
Externí odkaz:
https://doaj.org/article/4770d97b7ab3441897f9d30ce110c9ac
Publikováno v:
IEEE Access, Vol 8, Pp 197665-197683 (2020)
Automated vehicles make use of multiple sensors to detect their surroundings. Sensors have significantly improved over the years but still face challenges due to the presence of obstacles or adverse weather conditions, among others. Cooperative or co
Externí odkaz:
https://doaj.org/article/c07eceac66bc47d9843ce90df670330a
Publikováno v:
IEEE Access, Vol 7, Pp 143139-143159 (2019)
Network slicing is a novel 5G paradigm that exploits the virtualization and softwarization of networks to create different logical network instances over a common network infrastructure. Each instance is tailored for specific Quality of Service (QoS)
Externí odkaz:
https://doaj.org/article/8a3b881a2a7f4286ab303170104b4577
Autor:
M. Carmen Lucas-Estan, Javier Gozalvez
Publikováno v:
IEEE Access, Vol 7, Pp 113511-113524 (2019)
5G and beyond networks will offer multiple communication modes including device-to-device and multi-hop cellular (or UE-to-network relay) communications. Several studies have shown that these modes can significantly improve the Quality of Service (Qo
Externí odkaz:
https://doaj.org/article/7dec2a51e7c44a50827c19127213a042
Autor:
Javier Gozalvez
Publikováno v:
IEEE Vehicular Technology Magazine. 18:3-5
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7cc38267fe92b6959fcd05126db8050a
https://doi.org/10.1109/mvt.2023.3265791
https://doi.org/10.1109/mvt.2023.3265791
Autor:
M. Carmen Lucas-Estañ, Javier Gozalvez
Publikováno v:
IEEE Transactions on Vehicular Technology. 71:4171-4183
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7381149afcc9fe849aa21981d2adcffc
https://doi.org/10.1109/tvt.2021.3136725
https://doi.org/10.1109/tvt.2021.3136725