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2018
Conference Paper
Titel
Radar and Lidar Target Signatures of Various Object Types and Evaluation of Extended Object Tracking Methods for Autonomous Driving Applications
Abstract
This paper presents a novel discussion on comparison of common extended object tracking methods for estimating target-extension ellipses based on real world road level traffic data and a unique presentation on different target level signatures obtained for various object types such as cars, pedestrians and bicyclist obtained using automotive multi-mode radar network and 4x-Iayer automotive Iidar. The most commonly used extended object tracking methods are briefly introduced. In addition, measurement profiles of road users, car, cyclists, and pedestrians are investigated to compare each model and its assumptions with the real data. The obtained information can be further used to define the appropriate object specific and sensor specific measurement model. The measurement distribution is discussed in detail and compared with the models' assumptions. Extended object tracking is performed on the obtained data and performance analysis is carried out using high resolution ground truth. The evaluation is carried out separately on the radar and lidar data on exemplary traffic scenes. As a final step, a track-to-track intersection fusion approach is evaluated on the same data set to find out the different information gains. The relation between measurements and track behavior as well as other influences are discussed.