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dc.contributor.author
Yang, Kaidi
dc.contributor.author
Tan, Isabelle
dc.contributor.author
Menendez, Monica
dc.date.accessioned
2018-10-10T07:22:39Z
dc.date.available
2017-06-12T21:01:06Z
dc.date.available
2017-07-03T07:13:26Z
dc.date.available
2018-10-09T16:23:16Z
dc.date.available
2018-10-10T05:48:17Z
dc.date.available
2018-10-10T07:22:39Z
dc.date.issued
2017-05
dc.identifier.uri
http://hdl.handle.net/20.500.11850/130809
dc.identifier.doi
10.3929/ethz-b-000130809
dc.description.abstract
The emerging vehicle technologies, i.e. connected vehicle technology and autonomous driving technology, can be beneficial for traffic control and operations. They not only serve as new source of information, but also enable us to control and modify the trajectory of vehicles. Reinforcement learning is widely used to design intelligent control algorithms in various disciplines. This paper provides preliminary results on how the reinforcement learning methods perform in a connected vehicle environment.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
STRC
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
Reinforcement learning
en_US
dc.subject
Traffic signal control
en_US
dc.subject
Connected vehicle technology
en_US
dc.subject
Automated vehicles
en_US
dc.title
A reinforcement learning based traffic signal control algorithm in a connected vehicle environment
en_US
dc.type
Conference Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
ethz.size
16 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.event
17th Swiss Transport Research Conference (STRC 2017)
en_US
ethz.event.location
Ascona, Switzerland
en_US
ethz.event.date
May 17-19, 2017
en_US
ethz.notes
Conference paper only available online
en_US
ethz.publication.place
Ascona
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::08686 - Gruppe Strassenverkehrstechnik
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH::02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::08686 - Gruppe Strassenverkehrstechnik
en_US
ethz.date.deposited
2017-06-12T21:01:11Z
ethz.source
ECIT
ethz.identifier.importid
imp5936556f2d9ef86890
ethz.ecitpid
pub:193840
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-03T07:13:29Z
ethz.rosetta.lastUpdated
2018-10-10T07:22:44Z
ethz.rosetta.versionExported
true
ethz.COinS
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