New Performance Metrics for Lidar

Frame-rate measurement is so yesterday. Object-revisit rate and instantaneous resolution are more relevant metrics, and indicative of what a lidar system can and should do, argues a revolutionary in the artificial-perception space.

How do you measure the effectiveness of an intelligent, lidar-based perception system for autonomous vehicles? Conventional evaluation metrics favor frame rate and resolution as the ideal criteria. However, experts at Pleasanton, Calif.-based artificial perception company AEye believe that these criteria are inadequate for measuring the unique capabilities of more advanced lidar systems, nor do they explicitly address real-world problems facing autonomous driving, such as hazard detection and tracking.

“Makers of automotive lidar systems are frequently asked about their frame rate, and whether or not their technology has the ability to detect objects with 10% reflectivity at a specified range, frame rate and resolution,” said the company's co-founder and senior VP of engineering, Dr. Barry Behnken. “These metrics were established back in 2004 during the first DARPA Grand Challenge and haven't been altered since. Unfortunately, they fail to adequately rate a perception system's ability to perform safely on public roads, as the AVs back then were not being built for widespread use.”