Assessment and Benchmarking Approaches for 3D LiDAR Systems: A Comprehensive Overview

In the automotive industry's future, the advent of autonomous driving poses a significant challenge. A key component in this transformation is LiDAR (Light Detection and Ranging), which plays a fundamental role in environmental sensing. Over recent years, several new LiDAR systems have emerged on the market, reflecting the growing importance of this technology. Consequently, there is an urgent demand for tools to analyze and compare LiDAR systems specifically tailored to meet the automotive industry's needs. In recent years, researchers have proposed studies for analysing and benchmarking the performance of commercial LiDARs. In particular, three key aspects have been analysed for their importance: i) object detection capability and range, ii) robustness to different optical properties of objects, and iii) robustness to adverse weather conditions. Researchers have presented studies to characterize these aspects of an automotive LiDAR by proposing different approaches, setups and analyses. This paper provides a review of recent measurement approaches focusing on detection and ranging capability, noise resilience and adaptation to adverse weather conditions. Finally, the paper concludes with a discussion of proposed measurement methodologies and offers insights for potential future analyses in LiDAR assessment.