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dc.contributor.authorHorn, Berthold K. P.
dc.contributor.authorWang, Liang
dc.date.accessioned2019-06-03T15:16:11Z
dc.date.available2019-06-03T15:16:11Z
dc.date.issued2018-09
dc.identifier.issn1524-9050
dc.identifier.issn1558-0016
dc.identifier.urihttps://hdl.handle.net/1721.1/121194
dc.description.abstractTraffic congestion wastes fuel and commuters' time, and adds to CO₂ emissions. Stop-and-go traffic instabilities can be suppresses using bilateral control - which differs from 'car following' and adaptive cruise control in that, counter-intuitively, it uses information about the following vehicle (as well as about the leading vehicle). Stability can be proven mathematically, and can be demonstrated in simulation. A physical analog of a sequence of vehicles using bilateral control is a chain of masses connected by springs and dampers - a system which is inherently stable, since it lacks an external energy source. Here, in order to further understand bilateral control and its capacity to suppress instabilities, we move from a microscopic view (interaction of individual vehicles) to a macroscopic view (densities and flow rates). This leads us to the damped wave equation governing traffic under bilateral control. That equation allows us to determine the speed of propagation of disturbances, as well as their rate of decay. The equation is also useful in fine tuning parameters of bilateral control systems.en_US
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/tits.2017.2767595en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleWave Equation of Suppressed Traffic Flow Instabilitiesen_US
dc.typeArticleen_US
dc.identifier.citationHorn, Berthold K.P. and Liang Wang. "Wave Equation of Suppressed Traffic Flow Instabilities." IEEE Transactions on Intelligent Transportation Systems 19, 9 (September 2018): 2955 - 2964 © IEEEen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalIEEE Transactions on Intelligent Transportation Systemsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-05-31T11:58:31Z
dspace.date.submission2019-05-31T11:58:32Z
mit.journal.volume19en_US
mit.journal.issue9en_US


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