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dc.contributor.authorZapotecatl, Jorge L.
dc.contributor.authorRosenblueth, David A.
dc.contributor.authorGershenson Garcia, Carlos
dc.date.accessioned2017-06-07T14:03:16Z
dc.date.available2017-06-07T14:03:16Z
dc.date.issued2017-05
dc.identifier.issn1076-2787
dc.identifier.issn1099-0526
dc.identifier.urihttp://hdl.handle.net/1721.1/109699
dc.description.abstractSelf-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.en_US
dc.publisherHindawi Publishing Corporationen_US
dc.relation.isversionofhttp://dx.doi.org/10.1155/2017/7691370en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceHindawi Publishing Corporationen_US
dc.titleDeliberative Self-Organizing Traffic Lights with Elementary Cellular Automataen_US
dc.typeArticleen_US
dc.identifier.citationZapotecatl, Jorge L.; Rosenblueth, David A. and Gershenson, Carlos. "Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata." Complexity 2017, 7691370 (May 2017): 1-15 © 2017 Jorge L. Zapotecatl et alen_US
dc.contributor.departmentMassachusetts Institute of Technology. SENSEable City Laboratoryen_US
dc.contributor.mitauthorGershenson Garcia, Carlos
dc.relation.journalComplexityen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2017-06-07T08:22:24Z
dc.language.rfc3066en
dc.rights.holderCopyright © 2017 Jorge L. Zapotecatl et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dspace.orderedauthorsZapotecatl, Jorge L.; Rosenblueth, David A.; Gershenson, Carlosen_US
dspace.embargo.termsNen_US
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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