Zobrazeno 1 - 10
of 67
pro vyhledávání: '"David Fernández-Llorca"'
Publikováno v:
Engineering Proceedings, Vol 39, Iss 1, p 57 (2023)
The accurate prediction of road user behaviour is of paramount importance for the design and implementation of effective trajectory prediction systems. Advances in this domain have recently been centred on incorporating the social interactions betwee
Externí odkaz:
https://doaj.org/article/d731605bba86417f9acab60f700345ec
Autor:
Carlos Fernández, Jesús Muñoz-Bulnes, David Fernández-Llorca, Ignacio Parra, Iván García-Daza, Rubén Izquierdo, Miguel Á. Sotelo
Publikováno v:
Journal of Advanced Transportation, Vol 2018 (2018)
This paper addresses the problem of high-level road modeling for urban environments. Current approaches are based on geometric models that fit well to the road shape for narrow roads. However, urban environments are more complex and those models are
Externí odkaz:
https://doaj.org/article/e09df49eea2d49e189183cd42247b383
Publikováno v:
Journal of Advanced Transportation, Vol 2017 (2017)
A hybrid vision-map system is presented to solve the road detection problem in urban scenarios. The standardized use of machine learning techniques in classification problems has been merged with digital navigation map information to increase system
Externí odkaz:
https://doaj.org/article/251ceaf2dda34865b64822e119464692
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 10 (2013)
At present, the topic of automated vehicles is one of the most promising research areas in the field of Intelligent Transportation Systems (ITS). The use of automated vehicles for public transportation also contributes to reductions in congestion lev
Externí odkaz:
https://doaj.org/article/6196234b623644abbd20b50ee2726bed
Autor:
Iván García Daza, Rubén Izquierdo, Luis Miguel Martínez, Ola Benderius, David Fernández Llorca
Publikováno v:
Applied Intelligence. 53:12719-12735
The main challenge for the adoption of autonomous driving is to ensure an adequate level of safety. Considering the almost infinite variability of possible scenarios that autonomous vehicles would have to face, the use of autonomous driving simulator
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f825318343e9ce9b3c63f2ae7dd50fb
https://doi.org/10.1007/s10489-022-04148-1
https://doi.org/10.1007/s10489-022-04148-1
Autor:
Rubén Izquierdo, Álvaro Quintanar, David Fernández Llorca, Iván García Daza, Noelia Hernández, Ignacio Parra, Miguel Ángel Sotelo
Publikováno v:
Applied Intelligence. 53:8370-8388
This work presents a novel method for predicting vehicle trajectories in highway scenarios using efficient bird's eye view representations and convolutional neural networks. Vehicle positions, motion histories, road configuration, and vehicle interac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53ab8eedd79a1e050efcddb01174889b
https://doi.org/10.1007/s10489-022-03961-y
https://doi.org/10.1007/s10489-022-03961-y
New emerging technologies powered by Artificial Intelligence (AI) have the potential to disruptively transform our societies for the better. In particular, data-driven learning approaches (i.e., Machine Learning (ML)) have been a true revolution in t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3aecf6f5311bbead0f1e9692aaa3e3b3
Publikováno v:
IET Intelligent Transport Systems, Vol 15, Iss 8, Pp 987-1005 (2021)
The need to accurately estimate the speed of road vehicles is becoming increasingly important for at least two main reasons. First, the number of speed cameras installed worldwide has been growing in recent years, as the introduction and enforcement
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d40e966c31fd161023d526fd79be4f01
http://arxiv.org/abs/2101.06159
http://arxiv.org/abs/2101.06159
Autor:
H. Corrales, Ignacio Parra, Javier Lorenzo, A. Quintanar, Noelia Hernández, S. Vigre, David Fernández Llorca
Publikováno v:
Computer Aided Systems Theory – EUROCAST 2019 ISBN: 9783030450953
EUROCAST (2)
EUROCAST (2)
This paper describes an end-to-end training methodology for CNN-based fine-grained vehicle model classification. The method relies exclusively on images, without using complicated architectures. No extra annotations, pose normalization or part locali
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4d8d8ba43f7ffaeaa1802b8700af79a
https://doi.org/10.1007/978-3-030-45096-0_13
https://doi.org/10.1007/978-3-030-45096-0_13
Autor:
Miguel Angel Sotelo, Florian Wirth, Javier Lorenzo, Christoph Stiller, I. Parra, David Fernández Llorca
Publikováno v:
Web of Science
Pedestrian crossing prediction is a crucial task for autonomous driving. Numerous studies show that an early estimation of the pedestrian's intention can decrease or even avoid a high percentage of accidents. In this paper, different variations of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50e9e20f7809776463407617b238307a