02772nam 2200733z- 450 991055748660332120210501(CKB)5400000000042966(oapen)https://directory.doabooks.org/handle/20.500.12854/68522(oapen)doab68522(EXLCZ)99540000000004296620202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierAI-Based Transportation Planning and OperationBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online 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 and technologybicsscartificial neural networkautoencoderautomated vehicleblack icebottleneck and gridlock identificationCNNcontext-awarenessCycleGANdeep learningdeep neural networksdriving cycledynamic pricinggridlock predictionlink embeddinglink emission factorslong short-term memorymicro-level vehicle emission estimationMOVESpreventionpreventive automated driving systemreachability analysisreinforcement learningridesharingspatio-temporal datasupply improvementtaxitraffic accidentstraffic flow centralitytraffic speed predictiontraffic volumeurban road networkvehicle countingvehicle GPS dataHistory of engineering and technologySohn Keeminedt1289231Sohn KeeminothBOOK9910557486603321AI-Based Transportation Planning and Operation3021117UNINA