MicroVision’s perception software takes the massive amount of data and measurements from a vehicle’s sensor suite and abstracts the critical information. So, when the vehicle drives, the key information is easy to process and can be used for quick decision-making. For instance, if a car ahead is slowing down, the perception software processes this fact in split seconds and enables a timely response.
The integrated perception software works hand in hand with MicroVision’s sensors. MicroVision’s perception software is the brain behind small object detection, lane detection, road boundaries and dynamic object tracking and classification. Object recognition is at the core of perception, classifying objects and road users as well as small obstacles and overhanging load. This is achieved using sophisticated algorithms to interpret complex visual information from one or multiple lidar sensors. The software provides an incredibly accurate and detailed representation of the environment, enabling automakers to achieve a safe, reliable, and competitively advantageous driving application.
The integration of perception software into lidar sensors reduces power consumption because MicroVision uses a highly efficient SoC and optimizes the perception software for processing sensor measurements directly on the sensors. As external ECU hardware is expensive, this approach lowers costs and the system architecture is simplified as the sensor-specific perception processing is already done. These advantages allow the automaker to focus on the driving function.
DVN comment
MicroVision, with more than 350 employees and offices in Redmond, Detroit, Hamburg and Nuremberg, is a pioneer in MEMS-based laser beam scanning technology. They develop lidar sensors for the automotive industry and solutions for advanced driver assistance systems, autonomous vehicles, and other applications. With the acquisition of Ibeo Automotive Systems in January 2023, they are the only supplier with more than 50 years of combined experience on lidar’s technology and its integration in ADAS systems.
