Authors:
Amarin Kloeker
;
Robert Krajewski
and
Lutz Eckstein
Affiliation:
Institute for Automotive Engineering, RWTH Aachen University, Steinbachstr. 7, 52074 Aachen, Germany
Keyword(s):
Automated Driving, Trajectory Dataset, Drone, Infrastructure Sensors, ITS-S, Computer Vision.
Abstract:
Due to the complexity of automated vehicles, their development and validation require large amounts of naturalistic trajectory data of road users. In addition to the classical approach of using measurement vehicles to generate these data, approaches based on infrastructure sensors and drones have become increasingly popular. While advantages are postulated for each method, a practical comparison of the methods based on measurements of real traffic has so far been lacking. We present a theoretical and experimental analysis of two image-based measurement methods. For this purpose, we compare measurements of a drone-based system with a prototypical camera-based infrastructure sensor system. In addition to the detection statistics of the road users, the detection quality of both systems is also investigated using a reference vehicle equipped with an inertial navigation system. Through these experiments, we can confirm each approach’s advantages and disadvantages emerging from the theoret
ical analysis.
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