TY - GEN
T1 - Characterization and simulation of the effect of road dirt on the performance of a laser scanner
AU - Rivero, Jose Roberto Vargas
AU - Tahiraj, Ilir
AU - Schubert, Olaf
AU - Glassl, Christoph
AU - Buschardt, Boris
AU - Berk, Mario
AU - Chen, Jia
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Automotive environment sensors such as LIDARs (light detection and ranging) are the backbone of automated driving. It has to be made sure that the performance of these sensors is sufficient, even under adverse environment influences like accumulated dirt on a sensor cover. This paper describes the collection and analysis of real world road dirt samples, accumulated on the plastic cover of a LIDAR sensor. The effect of the dirt on the sensor performance is experimentally quantified by measuring the transmission and reflection properties of the dirty sensor plastic cover. Moreover, an analysis of the sensor's uncertainty in raw data position measurements is presented. Different alternatives to include these effects in a virtual simulation of the sensor are discussed. While the sample size of the dirty plastic covers is too small to representatively describe the effect of dirt on LIDAR performance, this study shows that an abstract effect on sensor performance such as dirt can be described, quantified and eventually be represented in a virtual simulation.
AB - Automotive environment sensors such as LIDARs (light detection and ranging) are the backbone of automated driving. It has to be made sure that the performance of these sensors is sufficient, even under adverse environment influences like accumulated dirt on a sensor cover. This paper describes the collection and analysis of real world road dirt samples, accumulated on the plastic cover of a LIDAR sensor. The effect of the dirt on the sensor performance is experimentally quantified by measuring the transmission and reflection properties of the dirty sensor plastic cover. Moreover, an analysis of the sensor's uncertainty in raw data position measurements is presented. Different alternatives to include these effects in a virtual simulation of the sensor are discussed. While the sample size of the dirty plastic covers is too small to representatively describe the effect of dirt on LIDAR performance, this study shows that an abstract effect on sensor performance such as dirt can be described, quantified and eventually be represented in a virtual simulation.
KW - LIDAR
KW - Laser scanner
KW - automated driving vehicle
KW - dirt
KW - sensor simulation
UR - http://www.scopus.com/inward/record.url?scp=85046250063&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2017.8317784
DO - 10.1109/ITSC.2017.8317784
M3 - Conference contribution
AN - SCOPUS:85046250063
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 1
EP - 6
BT - 2017 IEEE 20th International Conference on Intelligent Transportation Systems, ITSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017
Y2 - 16 October 2017 through 19 October 2017
ER -