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The recent years have witnessed tremendous growth in connected vehicles due to major interest in vehicular ad hoc networks (VANET) technology from both the research and industrial communities. VANET involves the generation of data from onboard sensors and its dissemination in other vehicles via vehicle-to-everything (V2X) communication, thus resulting in numerous applications such as steep-curve warnings. However, to increase the scope of applications, VANET has to integrate various technologies including sensor networks, which results in a new paradigm commonly referred to as vehicular sensor networks (VSN). Unlike traditional sensor networks, every node (vehicle) in VSN is equipped with various sensing (distance sensors, GPS, and cameras), storage, and communication capabilities, which can provide a wide range of applications including environmental surveillance and traffic monitoring. VSN has the potential to improve transportation technology and the transportation environment due to its unlimited power supply and resulting minimum energy constraints. However, VSN faces numerous challenges in terms of its design, implementation, network scalability, reliability, and deployment over large-scale networks, which need to be addressed before it is realized. This book comprises 12 outstanding research works related to vehicular sensor networks, addressing various aspects such as security, routing, SDN, and NDN.

barrier control --- sensors platform --- vehicle detection --- license plate recognition --- raspberry-pi --- features extraction --- machine learning algorithms --- connected vehicles, internet of vehicles --- security --- IoT --- blockchain --- vehicular ad-hoc network --- wireless sensor networks --- wake-up radio --- medium access control protocol --- receiver-initiated MAC protocol --- traffic adaptation --- software-defined vehicular network --- vehicle-to-everything (V2X) --- modeling and implementation --- software defined network --- information-centric networking (ICN) --- client-cache (CC) --- video on demand (VoD) --- vehicular sensor network (VSN) --- smart city --- delay tolerant network --- infrastructure offloading --- opportunistic network --- vehicular mobility --- energy consumption --- carbon emission --- V2V communication --- message contents plausibility --- power control --- vehicle edge computing --- 5G cellular networks --- multi-receiver signcryption --- privacy --- PSO --- genetic algorithm --- ITS --- UAV --- simulation --- dynamic positioning --- 3D placement --- vehicular communications --- cross-validation --- anti-collaborative attack --- resource-saving --- trust computing --- Caching --- Named Data Networking --- Information Centric Networking --- Vehicular Ad Hoc Networks --- 5G --- D2D communication --- vehicle-to-vehicle communication --- mode selection --- vehicular social network --- vehicular sensor networks (VSN) --- vehicular ad-hoc networks (VANET) --- privacy and trust --- cyber security --- multimedia and cellular communication --- emerging IoT applications in VANET and VSN --- blockchain within VANET and VSN

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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

History of engineering & technology --- 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

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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

History of engineering & technology --- 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