TY  - GEN
AU  - Fernández-Llorca,David
AU  - Parra Alonso,Ignacio
AU  - García Daza,Iván
AU  - Parra,Noelia Hernández
AU  - Fernández-Llorca,David
AU  - Parra Alonso,Ignacio
AU  - García Daza,Iván
AU  - Parra,Noelia Hernández
TI  - Intelligent Vehicles
SN  - books978-3-03943-403-9
PY  - 2020///
CY  - Basel, Switzerland
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - History of engineering & technology
KW  - bicssc
KW  - tracking-by-detection
KW  - multi-vehicle tracking
KW  - Siamese network
KW  - data association
KW  - Markov decision process
KW  - driving behavior
KW  - real-time monitoring
KW  - driver distraction
KW  - mobile application
KW  - portable system
KW  - simulation test
KW  - dynamic driving behavior
KW  - traffic scene augmentation
KW  - corridor model
KW  - IMU
KW  - vision
KW  - classification networks
KW  - Hough transform
KW  - lane markings detection
KW  - semantic segmentation
KW  - transfer learning
KW  - autonomous
KW  - off-road driving
KW  - tire-road forces estimation
KW  - slip angle estimation
KW  - gauge sensors
KW  - fuzzy logic system
KW  - load transfer estimation
KW  - simulation results
KW  - normalization
KW  - lateral force empirical model
KW  - driver monitor
KW  - lane departure
KW  - statistical process control
KW  - fault detection
KW  - sensor fault
KW  - signal restoration
KW  - intelligent vehicle
KW  - autonomous vehicle
KW  - kinematic model
KW  - visual SLAM
KW  - sparse direct method
KW  - photometric calibration
KW  - corner detection and filtering
KW  - loop closure detection
KW  - road friction coefficient
KW  - tire model
KW  - nonlinear observer
KW  - self-aligning torque
KW  - lateral displacement
KW  - Lyapunov method
KW  - automatic parking system (APS)
KW  - end-to-end parking
KW  - reinforcement learning
KW  - parking slot tracking
KW  - deceleration planning
KW  - multi-layer perceptron
KW  - smart regenerative braking
KW  - electric vehicles
KW  - vehicle speed prediction
KW  - driver behavior modeling
KW  - electric vehicle control
KW  - driver characteristics online learning
KW  - objects' edge detection
KW  - stixel histograms accumulate
KW  - point cloud segmentation
KW  - autonomous vehicles
KW  - scene understanding
KW  - occlusion reasoning
KW  - road detection
KW  - advanced driver assistance system
KW  - trajectory prediction
KW  - risk assessment
KW  - collision warning
KW  - connected vehicles
KW  - vehicular communications
KW  - vulnerable road users
KW  - fail-operational systems
KW  - fall-back strategy
KW  - automated driving
KW  - advanced driving assistance systems
KW  - illumination
KW  - shadow detection
KW  - shadow edge
KW  - image processing
KW  - traffic light detection
KW  - intelligent transportation system
KW  - lane-changing
KW  - merging maneuvers
KW  - game theory
KW  - decision-making
KW  - intelligent vehicles
KW  - model predictive controller
KW  - automatic train operation
KW  - softness factor
KW  - fusion velocity
KW  - online obtaining
KW  - hardware-in-the-loop simulation
KW  - driving assistant
KW  - driving diagnosis
KW  - accident risk maps
KW  - driving safety
KW  - intelligent driving
KW  - virtual test environment
KW  - millimeter wave radar
KW  - lane-change decision
KW  - risk perception
KW  - mixed traffic
KW  - minimum safe deceleration
KW  - automated driving system (ADS)
KW  - sensor fusion
KW  - multi-lane detection
KW  - particle filter
KW  - self-driving car
KW  - unscented Kalman filter
KW  - vehicle model
KW  - Monte Carlo localization
KW  - millimeter-wave radar
KW  - square-root cubature Kalman filter
KW  - Sage-Husa algorithm
KW  - target tracking
KW  - stationary and moving object classification
KW  - localization
KW  - LiDAR
KW  - GNSS
KW  - Global Positioning System (GPS)
KW  - monte carlo
KW  - autonomous driving
KW  - robot motion
KW  - path planning
KW  - piecewise linear approximation
KW  - multiple-target path planning
KW  - autonomous mobile robot
KW  - homotopy based path planning
KW  - LiDAR signal processing
KW  - sensor and information fusion
KW  - advanced driver assistance systems
KW  - autonomous racing
KW  - high-speed camera
KW  - real-time systems
KW  - LiDAR odometry
KW  - fail-aware
KW  - sensors
KW  - sensing
KW  - percepction
KW  - object detection and tracking
KW  - scene segmentation
KW  - vehicle positioning
KW  - fail-x systems
KW  - driver behavior modelling
KW  - automatic operation
N1  - Open Access
N2  - 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
UR  - https://mdpi.com/books/pdfview/book/3126
UR  - https://directory.doabooks.org/handle/20.500.12854/69334
ER  -