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Virtual traffic simulation with neural ...
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Document type :
Article dans une revue scientifique
DOI :
10.1016/j.advengsoft.2017.09.002
Title :
Virtual traffic simulation with neural network learned mobility model.
Author(s) :
Zhang, Jian [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
El Kamel, Abdelkader [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Journal title :
Advances in Engineering Software
Pages :
103-111
Publisher :
Elsevier
Publication date :
2018-01
ISSN :
0965-9978
English keyword(s) :
Modeling and simulation transportation system
Neural networks
Highway traffic
Mobility model
HAL domain(s) :
Informatique [cs]
English abstract : [en]
Virtual traffic simulation plays an important role in easing traffic congestion and reducing traffic pollution. As the transportation network expands, the former rule-based mobility models showed several limitations in ...
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Virtual traffic simulation plays an important role in easing traffic congestion and reducing traffic pollution. As the transportation network expands, the former rule-based mobility models showed several limitations in producing convincing virtual vehicles. A more realistic model with example-based method is in demand. In this paper, a neural network is employed with carefully selected traffic trajectory data. The virtual vehicle production is driven by the proposed mobility model and organized by a specified structure. Then, the virtual traffic simulation could be given for an indicated scenario.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
Harvested from HAL
Université de Lille

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