ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 49-56, 2015
https://doi.org/10.5194/isprsannals-II-3-W5-49-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
19 Aug 2015
ANALYSIS OF THE PERFORMANCE OF A LASER SCANNER FOR PREDICTIVE AUTOMOTIVE APPLICATIONS
J Zeisler1,2 and H.-G. Maas1 1Technische Universität Dresden, Institute of Photogrammetry and Remote Sensing, 01062 Dresden, Germany
2BMW Group, 80788 Munich, Germany
Keywords: LIDAR, Advanced Driver Assistance Systems, Object Detection, Bayesian Networks Abstract. In this paper we evaluate the use of a laser scanner for future advanced driver assistance systems. We focus on the important task of predicting the target vehicle for longitudinal ego vehicle control. Our motivation is to decrease the reaction time of existing systems during cut-in maneuvers of other traffic participants. A state-of-the-art laser scanner, the Ibeo Scala B2 R , is presented, providing its sensing characteristics and the subsequent high level object data output. We evaluate the performance of the scanner towards object tracking with the help of a GPS real time kinematics system on a test track. Two designed scenarios show phases with constant distance and velocity as well as dynamic motion of the vehicles. We provide the results for the error in position and velocity of the scanner and furthermore, review our algorithm for target vehicle prediction. Finally we show the potential of the laser scanner with the estimated error, that leads to a decrease of up to 40% in reaction time with best conditions.
Conference paper (PDF, 1261 KB)


Citation: Zeisler, J. and Maas, H.-G.: ANALYSIS OF THE PERFORMANCE OF A LASER SCANNER FOR PREDICTIVE AUTOMOTIVE APPLICATIONS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W5, 49-56, https://doi.org/10.5194/isprsannals-II-3-W5-49-2015, 2015.

BibTeX EndNote Reference Manager XML