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According to the National Research Council, the use of embedded systems throughout society could well overtake previous milestones in the information revolution. Mechatronics is the synergistic combination of electronic, mechanical engineering, controls, software and systems engineering in the design of processes and products. Mechatronic systems put “intelligence” into physical systems. Embedded sensors/actuators/processors are integral parts of mechatronic systems. The implementation of mechatronic systems is consistently on the rise. However, manufacturers are working hard to reduce the implementation cost of these systems while trying avoid compromising product quality. One way of addressing these conflicting objectives is through new automatic control methods, virtual sensing/estimation, and new innovative hardware topologies.

independent-wheel drive --- steering assistance --- nonlinear system --- active disturbance rejection control --- smooth road feeling --- city bus transport --- electric vehicles --- electrification --- software tool --- planning --- control --- charging management --- simulation --- analysis --- energy management --- hybrid electric vehicle --- powertrain electrification --- equivalent consumption minimization --- supercharging --- hardware-in-the-loop experiments --- driving force distribution --- decentralized traction system --- 4WD electric vehicle --- energy efficiency --- traction control --- efficiency optimization --- air mobility --- fuel cell hybrid aircraft --- stochastic optimal control --- drift counteraction optimal control --- normal force estimation --- unbiased minimum variance estimation --- controller output observer --- youla parameterization --- adaptive cruise control --- automated driving --- energy-saving --- fuel-saving --- optimal control --- passenger comfort --- new energy vehicles --- speed prediction --- macroscopic traffic model --- traffic big-data --- deep learning --- vehicle lateral dynamic and control --- unresolved issues --- application of speed prediction --- electric vehicle --- hybrid vehicle --- lithium ion --- ultracapacitor --- battery aging --- EHB --- EMB --- EWB --- system modeling --- bond graph --- optimization --- control design --- Youla parameterization --- robust control --- nonlinear optimization --- brake-by-wire --- actuator --- electro-mechanical brake --- electronic wedge brake --- electro-hydraulic brake --- n/a

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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 & technology --- autoencoder --- deep learning --- traffic volume --- vehicle counting --- CycleGAN --- bottleneck and gridlock identification --- gridlock prediction --- urban road network --- long short-term memory --- link embedding --- traffic speed prediction --- traffic flow centrality --- reachability analysis --- spatio-temporal data --- artificial neural network --- context-awareness --- dynamic pricing --- reinforcement learning --- ridesharing --- supply improvement --- taxi --- preventive automated driving system --- automated vehicle --- traffic accidents --- deep neural networks --- vehicle GPS data --- driving cycle --- micro-level vehicle emission estimation --- link emission factors --- MOVES --- black ice --- CNN --- prevention

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According to the National Research Council, the use of embedded systems throughout society could well overtake previous milestones in the information revolution. Mechatronics is the synergistic combination of electronic, mechanical engineering, controls, software and systems engineering in the design of processes and products. Mechatronic systems put “intelligence” into physical systems. Embedded sensors/actuators/processors are integral parts of mechatronic systems. The implementation of mechatronic systems is consistently on the rise. However, manufacturers are working hard to reduce the implementation cost of these systems while trying avoid compromising product quality. One way of addressing these conflicting objectives is through new automatic control methods, virtual sensing/estimation, and new innovative hardware topologies.

Technology: general issues --- History of engineering & technology --- independent-wheel drive --- steering assistance --- nonlinear system --- active disturbance rejection control --- smooth road feeling --- city bus transport --- electric vehicles --- electrification --- software tool --- planning --- control --- charging management --- simulation --- analysis --- energy management --- hybrid electric vehicle --- powertrain electrification --- equivalent consumption minimization --- supercharging --- hardware-in-the-loop experiments --- driving force distribution --- decentralized traction system --- 4WD electric vehicle --- energy efficiency --- traction control --- efficiency optimization --- air mobility --- fuel cell hybrid aircraft --- stochastic optimal control --- drift counteraction optimal control --- normal force estimation --- unbiased minimum variance estimation --- controller output observer --- youla parameterization --- adaptive cruise control --- automated driving --- energy-saving --- fuel-saving --- optimal control --- passenger comfort --- new energy vehicles --- speed prediction --- macroscopic traffic model --- traffic big-data --- deep learning --- vehicle lateral dynamic and control --- unresolved issues --- application of speed prediction --- electric vehicle --- hybrid vehicle --- lithium ion --- ultracapacitor --- battery aging --- EHB --- EMB --- EWB --- system modeling --- bond graph --- optimization --- control design --- Youla parameterization --- robust control --- nonlinear optimization --- brake-by-wire --- actuator --- electro-mechanical brake --- electronic wedge brake --- electro-hydraulic brake --- independent-wheel drive --- steering assistance --- nonlinear system --- active disturbance rejection control --- smooth road feeling --- city bus transport --- electric vehicles --- electrification --- software tool --- planning --- control --- charging management --- simulation --- analysis --- energy management --- hybrid electric vehicle --- powertrain electrification --- equivalent consumption minimization --- supercharging --- hardware-in-the-loop experiments --- driving force distribution --- decentralized traction system --- 4WD electric vehicle --- energy efficiency --- traction control --- efficiency optimization --- air mobility --- fuel cell hybrid aircraft --- stochastic optimal control --- drift counteraction optimal control --- normal force estimation --- unbiased minimum variance estimation --- controller output observer --- youla parameterization --- adaptive cruise control --- automated driving --- energy-saving --- fuel-saving --- optimal control --- passenger comfort --- new energy vehicles --- speed prediction --- macroscopic traffic model --- traffic big-data --- deep learning --- vehicle lateral dynamic and control --- unresolved issues --- application of speed prediction --- electric vehicle --- hybrid vehicle --- lithium ion --- ultracapacitor --- battery aging --- EHB --- EMB --- EWB --- system modeling --- bond graph --- optimization --- control design --- Youla parameterization --- robust control --- nonlinear optimization --- brake-by-wire --- actuator --- electro-mechanical brake --- electronic wedge brake --- electro-hydraulic brake

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Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.

Information technology industries --- spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition

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Smart cities operate under more resource-efficient management and economy than ordinary cities. As such, advanced business models have emerged around smart cities, which led to the creation of smart enterprises and organizations that depend on advanced technologies. This book includes 21 selected and peer-reviewed articles contributed in the wide spectrum of artificial intelligence applications to smart cities. Chapters refer to the following areas of interest: vehicular traffic prediction, social big data analysis, smart city management, driving and routing, localization, safety, health, and life quality.

Information technology industries --- spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition --- spatio-temporal --- residual networks --- bus traffic flow prediction --- advance rate --- shield performance --- principal component analysis --- ANFIS-GA --- tunnel --- online learning --- extreme learning machine --- cyclic dynamics --- transfer learning --- knowledge preservation --- Feature Adaptive --- optimization --- Bacterial Foraging algorithm --- Swarm Intelligence algorithm --- Isolated Microgrid --- traffic surveillance video --- state analysis --- Grassmann manifold --- neural network --- machine-learning --- quality of life --- Better Life Index --- bagging --- ensemble learning --- pedestrian attributes --- surveillance image --- semantic attributes recognition --- multi-label learning --- large-scale database --- traffic congestion detection --- minimizing traffic congestion --- traffic prediction --- deep learning --- urban mobility --- ITS --- Vehicle-to-Infrastructure --- neural networks --- LSTM --- embeddings --- trajectories --- motion behavior --- smart tourism --- driver’s behavior detection --- texting and driving --- convolutional neural network --- smart car --- smart cities --- smart infotainment --- driver distraction --- cameras --- convolution --- detection --- image recognition --- DSS --- diabetes prediction --- homecare assistance information system --- muti-attribute analysis --- artificial training dataset --- machine learning --- big data --- data analysis --- sensors --- Internet of Things --- vehicular networks --- VDTN --- routing --- message scheduling --- traffic flow prediction --- wavenet --- TrafficWave --- RNN --- GRU --- SAEs --- risk assessment --- neural architecture search --- recurrent neural network --- automated driving vehicle --- decision support system --- artificial intelligence --- disaster management --- Smart city --- program management --- integrated model --- smart city --- intelligence transportation system --- computer vision --- potential pedestrian safety --- data mining --- healthcare --- Apache Spark --- disease detection --- symptoms detection --- Arabic language --- Saudi dialect --- Twitter --- high performance computing (HPC) --- spatial-temporal dependencies --- traffic periodicity --- graph convolutional network --- traffic speed prediction --- vehicular traffic --- surveillance video --- big data analysis --- autonomous driving --- life quality --- pattern recognition