IEEE Consumer Electronics Magazine · 2018 · 359 citations · 16 references
ComputingAutomotive EngineeringAutonomous SystemsAutonomous VehiclesComputer VisionSensor FusionDecision-level FusionFeature-level FusionLidar PerceptionRobotic VisionVehicle PerceptionAdvanced Driver Assistance SystemsDriver Assistance SystemsFusion Of Heterogeneous SensorsObject Detection In Autonomous DrivingSensor Fusion For Vehicle ControlSensor Fusion HardwareSensor-level Fusion
ADASs are essential for vehicle safety and form the technological foundation of autonomous vehicles, with current systems largely vision‑based but increasingly incorporating lidar, radar, and other advanced sensors. This article surveys ADAS hardware and software technologies, outlining their capabilities and limitations, and identifies challenges for future ADAS development. The survey examines vision‑based recognition methods and sensor‑fusion techniques employed in ADAS solutions.
Advanced driver-assistance systems (ADASs) have become a salient feature for safety in modern vehicles. They are also a key underlying technology in emerging autonomous vehicles. State-of-the-art ADASs are primarily vision based, but light detection and ranging (lidar), radio detection and ranging (radar), and other advanced-sensing technologies are also becoming popular. In this article, we present a survey of different hardware and software ADAS technologies and their capabilities and limitations. We discuss approaches used for vision-based recognition and sensor fusion in ADAS solutions. We also highlight challenges for the next generation of ADASs.
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