Israel-based Innoviz Technologies, a leading provider of high-performance, solid-state LiDAR sensors and perception software has released its Automotive Perception Platform - InnovizAPP for the automotive industry.

The InnovizAPP is the company's advanced perception platform, which includes automotive-grade hardware and software that enable autonomous vehicles to identify and classify objects. The company is already shipping InnovizAPP to selected OEMs to accelerate timelines for consumer AV programs globally.

The InnovizAPP is based on the company’s advanced perception software, which leverages rich data derived from Innoviz's LiDAR sensors, coupled with proprietary AI algorithms, to analyse the point cloud and estimate an object's speed with high precision. The software can accurately detect and classify objects in any 3D driving scene up to 250 meters away, including cars, trucks, motorcycles, pedestrians, and more. It also executes perception algorithms in real time, detecting and classifying pixels as collision relevant or non-collision relevant.

The hardware provides an automotive-grade reference design based on low-cost automotive-grade components. It connects to existing vehicle systems and enables real-time perception in a simple plug-and-play manner, allowing automakers to test and learn how to build their own autonomous driving systems.

Omar Keilaf, CEO and co-founder, Innoviz said: "InnovizAPP is a true technology breakthrough, offering an adaptable automotive-grade chip and platform that can be incorporated into existing vehicles. We developed it in response to requests from major automakers, and our customers in Asia, Europe, and North America are already optimising their AV programs with this platform, which is rapidly becoming the gold standard for customer validation."

Both the perception software and Innoviz's solid-state LiDAR sensor, InnovizOne, are designed and developed to conform with the automotive industry's highest standards and are being adopted by key industry leaders, including BMW.