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010   $a3-642-54771-0
024 7 $a10.1007/978-3-642-54771-3
035   $a(CKB)3710000000751170
035   $a(DE-He213)978-3-642-54771-3
035   $a(MiAaPQ)EBC4592163
035   $a(PPN)194512525
035   $a(EXLCZ)993710000000751170
100   $a20160713d2017      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aTraffic Networks as Information Systems $eA Viability Approach /$fby Jean-Pierre Aubin, Anya Désilles
205   $a1st ed. 2017.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2017.
215   $a1 online resource (XVI, 246 p. 39 illus., 37 illus. in color.) 
225 1 $aMathematical Engineering,$x2192-4732
311   $a3-642-54770-2 
320   $aIncludes bibliographical references and indexes.
327   $a1 Introduction -- 2 Celerity Regulators on Networks -- 3 Traveling on the Network -- 4 Viability Characterizations and Construction of Celerity Regulators .
330   $aThis authored monograph covers a viability to approach to  traffic management by advising to vehicles circulated on the network the velocity they should follow for satisfying global traffic conditions;. It presents an investigation of three structural innovations:   The objective is to broadcast at each instant and at each position the advised celerity to vehicles, which could be read by auxiliary speedometers or used by cruise control devices.   Namely,  1. Construct regulation feedback providing at each time and position advised velocities (celerities)   for minimizing congestion or other requirements. 2. Taking into account traffic constraints of different type, the first one being to remain on the roads, to stop at junctions, etc. 3. Use information provided by the probe vehicles equipped with GPS to the traffic regulator; 4. Use other global traffic measures of vehicles provided by different types of sensors;   These results are based on convex analysis, intertemporal optimization and viability theory as mathematical tools as well as viability algorithms on the computing side, instead of conventional techniques such as partial differential equations and their resolution by finite difference or finite elements algorithms. The target audience primarily covers researchers and mathematically oriented engineers but the book may also be beneficial for graduate students.
410  0$aMathematical Engineering,$x2192-4732
606   $aComputational complexity
606   $aMathematical optimization
606   $aRegional economics
606   $aSpatial economics
606   $aApplication software
606   $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022
606   $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008
606   $aRegional/Spatial Science$3https://scigraph.springernature.com/ontologies/product-market-codes/W49000
606   $aComputer Appl. in Administrative Data Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/I2301X
615  0$aComputational complexity.
615  0$aMathematical optimization.
615  0$aRegional economics.
615  0$aSpatial economics.
615  0$aApplication software.
615 14$aComplexity.
615 24$aOptimization.
615 24$aRegional/Spatial Science.
615 24$aComputer Appl. in Administrative Data Processing.
676   $a338.31
700   $aAubin$b Jean-Pierre$4aut$4http://id.loc.gov/vocabulary/relators/aut$054013
702   $aDésilles$b Anya$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910254347903321
996   $aTraffic Networks as Information Systems$92199637
997   $aUNINA