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Intelligent transportation systems --- Electronics in transportation --- Electronics in transportation. --- Intelligent transportation systems. --- Advanced Road Traffic Systems --- Advanced Transport Telematics --- ATT (Highway communications) --- Intelligent Road Transportation Systems --- Intelligent Vehicle Highway Systems --- IRTS (Highway communications) --- ITS (Highway communications) --- IVHS (Highway communications) --- Road Transport Informatics --- RTI (Highway communications) --- Vehicle Information and Communication Systems --- VICS (Highway communications) --- Highway communications --- Mobile communication systems --- Transportation --- Sociotechnical systems --- Transportation Engineering --- Communication route-véhicule --- Electronique dans le transport --- Periodicals. --- Périodiques --- Engineering --- Automobile and Transportation --- smart public transport --- autonomous and intelligent vehicles --- traffic modelling --- big data --- machine learning --- artificial intelligence --- Intelligent Vehicle Highway Systems - Periodicals --- Electronics in transportation - Periodicals

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Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens.

Technology: general issues --- History of engineering & technology --- star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance --- star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance

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This book summarizes the latest developments in the area of human factors test and evaluation methods for automated vehicles. Future vehicles will allow a transition of responsibility from the driver to the automated driving system and vice versa. Drivers will have the opportunity to use a wide variety of different driver assistance systems within the same vehicle. This coexistence of different automation levels creates new challenges in the design of the vehicle’s human–machine interface (HMI), which have to be accounted for by human factors experts, both in industrial design and in academia. This book brings together the latest developments, empirical evaluations and guidelines on various topics, such as the design and evaluation of interior as well as exterior HMIs for automated vehicles, and the assessment of the impact of automated vehicles on non-automated road users and driver state assessment (e.g., fatigue, motion sickness, fallback readiness) during automated driving.

History of engineering & technology --- virtual reality --- automated driving --- pedestrians --- decision making --- crossing --- eHMI --- eye-tracking --- attention distribution --- road safety --- driverless vehicles --- behavioural adaptation --- SAE L3 motorway chauffeur --- system usage --- acceptance --- attention --- secondary task --- highly automated driving --- HAD --- takeover --- conditional automation --- intelligent vehicles --- objective complexity --- subjective complexity --- familiarity --- cognitive assistance --- takeover quality --- standardized test procedure --- use cases --- test protocol --- Adaptive HMI --- automotive user interfaces --- driver behaviour --- automated vehicles --- automated driving systems --- HMI --- guidelines --- heuristic evaluation --- checklist --- expert evaluation --- human-machine interface --- mode awareness --- conditionally automated driving --- human–machine interface --- usability --- validity --- method development --- motion sickness --- methodology --- driving comfort --- multi-vehicle simulation --- mixed traffic --- measurement method --- SAE Level 2 --- SAE Level 3 --- human factors --- human machine interface --- controllability --- L3Pilot --- marking automated vehicles --- automated vehicles―human drivers interaction --- explicit communication --- external human-machine interface --- (automated) vehicle–pedestrian interaction --- implicit communication --- Wizard of Oz --- video --- setup comparison/method comparison --- partially automated driving --- non-driving related tasks --- take-over situations --- test protocol development --- user studies (simulator --- closed circuit) --- sleep --- sleep inertia --- HMI design --- external human–machine interface --- interface size --- legibility --- spatiotemporal displays --- sensory augmentation --- reliability display --- uncertainty encoding --- automotive hmi --- human-machine cooperation --- cooperative driver assistance --- state transparency display --- self-driving vehicles --- test methods --- evaluation --- user studies --- driver state --- discomfort --- psychophysiology --- heart-rate variability (HRV) --- skin conductance response (SCR) --- highly automated driving (HAD) --- virtual reality --- automated driving --- pedestrians --- decision making --- crossing --- eHMI --- eye-tracking --- attention distribution --- road safety --- driverless vehicles --- behavioural adaptation --- SAE L3 motorway chauffeur --- system usage --- acceptance --- attention --- secondary task --- highly automated driving --- HAD --- takeover --- conditional automation --- intelligent vehicles --- objective complexity --- subjective complexity --- familiarity --- cognitive assistance --- takeover quality --- standardized test procedure --- use cases --- test protocol --- Adaptive HMI --- automotive user interfaces --- driver behaviour --- automated vehicles --- automated driving systems --- HMI --- guidelines --- heuristic evaluation --- checklist --- expert evaluation --- human-machine interface --- mode awareness --- conditionally automated driving --- human–machine interface --- usability --- validity --- method development --- motion sickness --- methodology --- driving comfort --- multi-vehicle simulation --- mixed traffic --- measurement method --- SAE Level 2 --- SAE Level 3 --- human factors --- human machine interface --- controllability --- L3Pilot --- marking automated vehicles --- automated vehicles―human drivers interaction --- explicit communication --- external human-machine interface --- (automated) vehicle–pedestrian interaction --- implicit communication --- Wizard of Oz --- video --- setup comparison/method comparison --- partially automated driving --- non-driving related tasks --- take-over situations --- test protocol development --- user studies (simulator --- closed circuit) --- sleep --- sleep inertia --- HMI design --- external human–machine interface --- interface size --- legibility --- spatiotemporal displays --- sensory augmentation --- reliability display --- uncertainty encoding --- automotive hmi --- human-machine cooperation --- cooperative driver assistance --- state transparency display --- self-driving vehicles --- test methods --- evaluation --- user studies --- driver state --- discomfort --- psychophysiology --- heart-rate variability (HRV) --- skin conductance response (SCR) --- highly automated driving (HAD)

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Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens.

Technology: general issues --- History of engineering & technology --- star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance

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Recent trends in vehicle engineering are testament to the great efforts that scientists and industries have made to seek solutions to enhance both the performance and safety of vehicular systems. This Special Issue aims to contribute to the study of modern vehicle dynamics, attracting recent experimental and in-simulation advances that are the basis for current technological growth and future mobility. The area involves research, studies, and projects derived from vehicle dynamics that aim to enhance vehicle performance in terms of handling, comfort, and adherence, and to examine safety optimization in the emerging contexts of smart, connected, and autonomous driving.This Special Issue focuses on new findings in the following topics:(1) Experimental and modelling activities that aim to investigate interaction phenomena from the macroscale, analyzing vehicle data, to the microscale, accounting for local contact mechanics; (2) Control strategies focused on vehicle performance enhancement, in terms of handling/grip, comfort and safety for passengers, motorsports, and future mobility scenarios; (3) Innovative technologies to improve the safety and performance of the vehicle and its subsystems; (4) Identification of vehicle and tire/wheel model parameters and status with innovative methodologies and algorithms; (5) Implementation of real-time software, logics, and models in onboard architectures and driving simulators; (6) Studies and analyses oriented toward the correlation among the factors affecting vehicle performance and safety; (7) Application use cases in road and off-road vehicles, e-bikes, motorcycles, buses, trucks, etc.

Technology: general issues --- History of engineering & technology --- tire model parameters identification --- artificial neural networks --- curve fitting --- Pacejka’s magic formula --- intelligent vehicles --- autonomous vehicles --- microscopic traffic simulation --- autonomous driving --- friction estimate --- tire-based control --- ADAS --- potential friction --- energy consumption and recovery --- transmission layouts --- fuel-cell electric vehicles --- adhesion enhancement --- dimple model --- patterned surfaces --- viscoelasticity --- enhancement --- articulated vehicles --- stability analysis --- nonlinear dynamic model --- snake instability --- eigenvalue analysis --- central control --- non-linear model-based predictive control --- pitch behavior --- predictive control --- roll behavior --- self-steering behavior --- vehicle dynamics --- viscoelastic modulus --- rubber --- friction --- empirical modeling --- autonomous emergency steering --- multi-input multi-output model predictive control --- actuator dynamics --- control allocation --- handling enhancement --- road friction --- wear --- tyre --- suspension --- semi-active --- handling --- comfort --- optimisation --- directional stability --- road profile --- road unevenness --- vehicle-road interaction --- vertical vehicle excitation --- tire models --- tire tread --- motorcycle --- rider --- screw axis --- weave --- wobble --- multibody --- gravel pavement --- roughness --- straightedge --- power spectral density --- international roughness index --- vehicle response --- driving comfort --- sky-hook --- in-wheel motor --- semi-active suspension --- quarter-car model --- suspension performance --- suspension test bench --- vehicle stability --- road models --- quarter car models --- limit cycles --- acceleration speed portraits --- speed oscillations --- velocity bifurcations --- noisy limit cycles --- limit flows of trajectories --- Sommerfeld effects --- differential-algebraic systems --- polar coordinates of roads --- covariance equations --- stability in mean --- supercritical speeds --- analytical travel speed amplitudes --- Floquet theory applied to limit cycles --- non-pneumatic tire --- finite element analysis --- steady state analysis --- tire characterization --- footprint --- contact patch --- longitudinal interaction --- n/a --- Pacejka's magic formula