Survey of State-of-Art Autonomous Driving Technologies with Deep Learning
Yu Huang, Yue Chen
Abstract
This is a survey of autonomous driving technologies with deep learning methods. We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc. Due to the limited space, we focus the analysis on several key areas, i.e. 3D object detection, depth estimation from cameras, multiple sensor fusion on the data, feature and task level respectively, behavior modelling and prediction of vehicle driving and pedestrian trajectories.
Topics & Concepts
Computer scienceDeep learningArtificial intelligenceSensor fusionTask (project management)PedestrianObject detectionFocus (optics)PerceptionComputer visionKey (lock)Feature (linguistics)Feature extractionMachine learningPattern recognition (psychology)EngineeringTransport engineeringComputer securitySystems engineeringPhilosophyLinguisticsPhysicsOpticsNeuroscienceBiologyAutonomous Vehicle Technology and SafetyVideo Surveillance and Tracking MethodsAdvanced Vision and Imaging