02751nam 2200721z- 450 991055748660332120231214133029.0(CKB)5400000000042966(oapen)https://directory.doabooks.org/handle/20.500.12854/68522(EXLCZ)99540000000004296620202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAI-Based Transportation Planning and OperationBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic resource (124 p.)3-0365-0364-1 3-0365-0365-X The purpose of this Special Issue is to create an an academic platform whereby high-quality research papers are published on the applications of innovative AI algorithms to transportation planning and operation. The authors present their original research articles related to the applications of AI or machine-learning techniques to transportation planning and operation. The topics of the articles encompass traffic surveillance, traffic safety, vehicle emission reduction, congestion management, traffic speed forecasting, and ride sharing strategy.History of engineering & technologybicsscautoencoderdeep learningtraffic volumevehicle countingCycleGANbottleneck and gridlock identificationgridlock predictionurban road networklong short-term memorylink embeddingtraffic speed predictiontraffic flow centralityreachability analysisspatio-temporal dataartificial neural networkcontext-awarenessdynamic pricingreinforcement learningridesharingsupply improvementtaxipreventive automated driving systemautomated vehicletraffic accidentsdeep neural networksvehicle GPS datadriving cyclemicro-level vehicle emission estimationlink emission factorsMOVESblack iceCNNpreventionHistory of engineering & technologySohn Keeminedt1289231Sohn KeeminothBOOK9910557486603321AI-Based Transportation Planning and Operation3021117UNINA