Intelligent Vehicles

• Autore: Fernández-Llorca David
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
• Descrizione fisica: 1 electronic resource (752 p.)
• Soggetto topico: History of engineering & technology
• Soggetto non controllato: tracking-by-detection; multi-vehicle tracking; Siamese network; data association; Markov decision process; driving behavior; real-time monitoring; driver distraction; mobile application; portable system; simulation test; dynamic driving behavior; traffic scene augmentation; corridor model; IMU; vision; classification networks; Hough transform; lane markings detection; semantic segmentation; transfer learning; autonomous; off-road driving; tire-road forces estimation; slip angle estimation; gauge sensors; fuzzy logic system; load transfer estimation; simulation results; normalization; lateral force empirical model; driver monitor; lane departure; statistical process control; fault detection; sensor fault; signal restoration; intelligent vehicle; autonomous vehicle; kinematic model; visual SLAM; sparse direct method; photometric calibration; corner detection and filtering; loop closure detection; road friction coefficient; tire model; nonlinear observer; self-aligning torque; lateral displacement; Lyapunov method; automatic parking system (APS); end-to-end parking; reinforcement learning; parking slot tracking; deceleration planning; multi-layer perceptron; smart regenerative braking; electric vehicles; vehicle speed prediction; driver behavior modeling; electric vehicle control; driver characteristics online learning; objects’ edge detection; stixel histograms accumulate; point cloud segmentation; autonomous vehicles; scene understanding; occlusion reasoning; road detection; advanced driver assistance system; trajectory prediction; risk assessment; collision warning; connected vehicles; vehicular communications; vulnerable road users; fail-operational systems; fall-back strategy; automated driving; advanced driving assistance systems; illumination; shadow detection; shadow edge; image processing; traffic light detection; intelligent transportation system; lane-changing; merging maneuvers; game theory; decision-making; intelligent vehicles; model predictive controller; automatic train operation; softness factor; fusion velocity; online obtaining; hardware-in-the-loop simulation; driving assistant; driving diagnosis; accident risk maps; driving safety; intelligent driving; virtual test environment; millimeter wave radar; lane-change decision; risk perception; mixed traffic; minimum safe deceleration; automated driving system (ADS); sensor fusion; multi-lane detection; particle filter; self-driving car; unscented Kalman filter; vehicle model; Monte Carlo localization; millimeter-wave radar; square-root cubature Kalman filter; Sage-Husa algorithm; target tracking; stationary and moving object classification; localization; LiDAR; GNSS; Global Positioning System (GPS); monte carlo; autonomous driving; robot motion; path planning; piecewise linear approximation; multiple-target path planning; autonomous mobile robot; homotopy based path planning; LiDAR signal processing; sensor and information fusion; advanced driver assistance systems; autonomous racing; high-speed camera; real-time systems; LiDAR odometry; fail-aware; sensors; sensing; percepction; object detection and tracking; scene segmentation; vehicle positioning; fail-x systems; driver behavior modelling; automatic operation
• 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