The autonomous vehicle industry and OEM are designing improved vehicles that are more adaptable to environmental conditions like fog and poor lighting through smart radar solutions.
FREMONT, CA: Smart radar solutions are important for safe autonomous vehicular functioning. Traditionally, autonomous vehicle manufacturers and designers focus on physical radar technology regardless of the hardware's increased costs, size, and power capacity. Digitally enhancing radar capacity, like connecting radar applications to machine learning (ML), makes the overall production and quality of autonomous vehicles cost-effective through high-resolution and long-range sensor capabilities.
Smart radar solutions contribute to a more effective vehicular perception. Integrating software solutions and mechanical improvements are important to autonomous vehicles' safety, marketability, and cost-effective production and scalability.
Artificial intelligence (AI) powered radar technology has the following benefits:
Replacing lidar with AI-powered radar: Lidar sensors are ineffective in certain events like nighttime. The quality of lidar-guided camera vision degrades greatly in the dark and fog, resulting in potential vehicular failure. Radar sensors function in all environmental conditions and have been tested in military settings.
Improving radar perceptions involves installing more physical features like antennae, increasing the overall cost and vehicle size. Software solutions improve performance while reducing overall costs.
Optimizing radar solutions with AI: ML-integrated devices facilitate the radar sensor's adaptive phase-modulated waveform and increase the sensor's resolution by 100. Adaptive phase-modulated waveform-based sensors adapt to the environment without installing antennae. It improves resolution range and perception without installing additional hardware and limiting the cost of upgrading to ML-based radar solutions.
Smart radar: The autonomous vehicle industry aims to produce more vehicles with advanced perception, size, power, performance, and scaled radar solutions. Smart radars improve their functionality and adaptability to their environment through ML algorithms. The automotive industry has advanced vehicular perception over time. Original equipment manufacturers (OEM) are designing algorithms for sensors to identify pedestrians, objects, and other vehicles. AI-based sensors are important developments as AI-based vehicular perception can generate images with high resolution per frame. It can identify targets from hundreds of meters away, allowing for greater occupant and vehicular safety.