Measurement Error Simulation for Lidar

Abstract

Autonomous vehicles require plenty of testing and validation, and simulation environments are a good choice for validation since they enable the testing of multiple scenarios. One of the most common sensors in the field is the Lidar sensor, which allows the retrieval of 3D information from the environment, often used with other sensors and cameras. Measurement errors become important when using a Lidar sensor with other sensors. However, these errors are not correctly included or modeled in most simulation environments. This thesis work aims to explore how measurement errors can be included in the simulation environment. A model was developed to find the error’s standard deviation depending on the target material’s reflectivity and distance and applied with the Weierstrass fractal function to model the repetitive behavior of the error. Results show that Weierstrass fractal function was appropriate for modeling the repetitive behavior. The model developed for the standard deviation of the error was working well in close distances, while further experimentation was needed for long ranges.