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Optimal control based heuristic for congestion reduction in traffic networks
(Planta Piloto de Ingeniería Química, 2013-01)
The principal purpose of this work is to test the TUC strategy in a simple case using a micro-simulator designed ad hoc, previous to its real implementation. Using concepts of traffic engineering we describe a well known ...
Statistical attribution of errors in urban noise modeling
(Elsevier Ltd, 2019)
Modeling traffic through a sequence of traffic lights
(AMERICAN PHYSICAL SOCIETY, 2004)
Evaluation of algorithms for traffic sign detection
(2019-09)
Traffic sign detection is a crucial task in autonomous driving systems. Due to its importance, several techniques have been used to solve this problem. In this work, the three more common approaches are evaluated. The first ...
Optical router model under correlated and non-uniform traffic
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2003-12-01)
A detailed analytical traffic model for all-optical wavelength division multiplexing (WDM) photonic packet-switched router is presented and the requirements for buffer size are analyzed. Also it is known that due to the ...
Development of a deep learning model for recognising traffic sings focused on difficult cases
The automotive industry is expanding its efforts to develop new techniques for increasing the level of intelligent driving and create new autonomous cars capable of driving with more intelligent capabilities. Thus, companies ...
Simulação e otimização da programação semafórica de uma região de Curitiba
(Universidade Tecnológica Federal do ParanáCuritibaBrasilDepartamento Acadêmico de InformáticaEngenharia da ComputaçãoUTFPR, 2015-07-15)
The traffic light control in Curitiba is currently held by the Municipal Operational Control Center. The city is divided into 33 different semaphoric regions, each with one specific timing table. In the Control Center, ...
Traffic model with an absorbing-state phase transition
(Universidade Federal de Minas GeraisBrasilICX - DEPARTAMENTO DE FÍSICAUFMG, 2017-02-06)