Automotive Lidar Modelling Approach Based on Material Properties and Lidar Capabilities

Sensors
Stefan MuckenhuberZrinka Bockaj

Abstract

Development and validation of reliable environment perception systems for automated driving functions requires the extension of conventional physical test drives with simulations in virtual test environments. In such a virtual test environment, a perception sensor is replaced by a sensor model. A major challenge for state-of-the-art sensor models is to represent the large variety of material properties of the surrounding objects in a realistic manner. Since lidar sensors are considered to play an essential role for upcoming automated vehicles, this paper presents a new lidar modelling approach that takes material properties and corresponding lidar capabilities into account. The considered material property is the incidence angle dependent reflectance of the illuminated material in the infrared spectrum and the considered lidar property its capability to detect a material with a certain reflectance up to a certain range. A new material classification for lidar modelling in the automotive context is suggested, distinguishing between 7 material classes and 23 subclasses. To measure angle dependent reflectance in the infrared spectrum, a new measurement device based on a time of flight camera is introduced and calibrated using Lamb...Continue Reading

References

Jan 10, 2002·Applied Microbiology and Biotechnology·K B RietherP Billard
Nov 10, 2016·Optics Express·Gunzung Kim, Yongwan Park

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Citations

Mar 7, 2021·Sensors·Federico CavedoMichele Norgia
Apr 4, 2021·Sensors·De Jong YeongJoseph Walsh

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Methods Mentioned

BETA
chip

Software Mentioned

Open Simulation Interface ( OSI )
Vires VTD
CARLA
Ouster OS -
Ouster OS
IPG CarMaker
Leica
AirSim
SphereOptics
Velodyne Alpha Prime

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