Intelligent Vehicles

• Autore: Fernández-Llorca David
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 online resource (752 p.)
• Soggetto topico: History of engineering and technology
• Soggetto non controllato: accident risk maps; advanced driver assistance system; advanced driver assistance systems; advanced driving assistance systems; automated driving; automated driving system (ADS); automatic operation; automatic parking system (APS); automatic train operation; autonomous; autonomous driving; autonomous mobile robot; autonomous racing; autonomous vehicle; autonomous vehicles; classification networks; collision warning; connected vehicles; corner detection and filtering; corridor model; data association; deceleration planning; decision-making; driver behavior modeling; driver behavior modelling; driver characteristics online learning; driver distraction; driver monitor; driving assistant; driving behavior; driving diagnosis; driving safety; dynamic driving behavior; electric vehicle control; electric vehicles; end-to-end parking; fail-aware; fail-operational systems; fail-x systems; fall-back strategy; fault detection; fusion velocity; fuzzy logic system; game theory; gauge sensors; Global Positioning System (GPS); GNSS; hardware-in-the-loop simulation; high-speed camera; homotopy based path planning; Hough transform; illumination; image processing; IMU; intelligent driving; intelligent transportation system; intelligent vehicle; intelligent vehicles; kinematic model; lane departure; lane markings detection; lane-change decision; lane-changing; lateral displacement; lateral force empirical model; LiDAR; LiDAR odometry; LiDAR signal processing; load transfer estimation; localization; loop closure detection; Lyapunov method; Markov decision process; merging maneuvers; millimeter wave radar; millimeter-wave radar; minimum safe deceleration; mixed traffic; mobile application; model predictive controller; monte carlo; Monte Carlo localization; multi-lane detection; multi-layer perceptron; multi-vehicle tracking; multiple-target path planning; nonlinear observer; normalization; object detection and tracking; objects' edge detection; occlusion reasoning; off-road driving; online obtaining; parking slot tracking; particle filter; path planning; percepction; photometric calibration; piecewise linear approximation; point cloud segmentation; portable system; real-time monitoring; real-time systems; reinforcement learning; risk assessment; risk perception; road detection; road friction coefficient; robot motion; Sage-Husa algorithm; scene segmentation; scene understanding; self-aligning torque; self-driving car; semantic segmentation; sensing; sensor and information fusion; sensor fault; sensor fusion; sensors; shadow detection; shadow edge; Siamese network; signal restoration; simulation results; simulation test; slip angle estimation; smart regenerative braking; softness factor; sparse direct method; square-root cubature Kalman filter; stationary and moving object classification; statistical process control; stixel histograms accumulate; target tracking; tire model; tire-road forces estimation; tracking-by-detection; traffic light detection; traffic scene augmentation; trajectory prediction; transfer learning; unscented Kalman filter; vehicle model; vehicle positioning; vehicle speed prediction; vehicular communications; virtual test environment; vision; visual SLAM; vulnerable road users
• Persona (resp. second.): Parra AlonsoIgnacio; García DazaIván; ParraNoelia Hernández; Fernández-LlorcaDavid
• Sommario/riassunto: This book presents the results of the successful Sensors Special Issue on Intelligent Vehicles that received submissions between March 2019 and May 2020. The Guest Editors of this Special Issue are Dr. David Fernández-Llorca, Dr. Ignacio Parra-Alonso, Dr. Iván García-Daza and Dr. Noelia Parra-Alonso, all from the Computer Engineering Department at the University of Alcalá (Madrid, Spain). A total of 32 manuscripts were finally accepted between 2019 and 2020, presented by top researchers from all over the world. The reader will find a well-representative set of current research and developments related to sensors and sensing for intelligent vehicles. The topics of the published manuscripts can be grouped into seven main categories: (1) assistance systems and automatic vehicle operation, (2) vehicle positioning and localization, (3) fault diagnosis and fail-x systems, (4) perception and scene understanding, (5) smart regenerative braking systems for electric vehicles, (6) driver behavior modeling and (7) intelligent sensing. We, the Guest Editors, hope that the readers will find this book to contain interesting papers for their research, papers that they will enjoy reading as much as we have enjoyed organizing this Special Issue
• Titolo autorizzato: Intelligent Vehicles
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557112303321
• Lo trovi qui: Univ. Federico II