Paper Info
Title
Inter-vehicle object association for cooperative perception systems
Abstract
In cooperative perception systems, different vehicles share object data obtained by their local environment perception sensors, like radar or lidar, via wireless communication. Inaccurate self-localizations of the vehicles complicate association of locally perceived objects and objects detected and transmitted by other vehicles. In this paper, a method for inter-vehicle object association is presented. Position and orientation offsets between object lists from different vehicles are estimated by applying point matching algorithms. Different algorithms are analyzed in simulations concerning their robustness and performance. Results with a first implementation of the so-called Auction-ICP algorithm in a real test vehicle validate the simulation results.
Year
DOI
Venue
2013
10.1109/ITSC.2013.6728345
ITSC
Keywords
Field
DocType
cooperative systems,driver information systems,iterative methods,object detection,pattern matching,sensor fusion,auction-icp algorithm,cooperative perception systems,intervehicle object association,iterative closest point algorithm,local environment perception sensors,locally perceived object association,object data sharing,orientation offsets,point matching algorithms,position offsets,simulation,algorithms,intelligent transportation systems,data collection
Radar,Computer vision,Object detection,Point set registration,Wireless,Simulation,Computer science,Sensor fusion,Robustness (computer science),Artificial intelligence,Intelligent transportation system,Pattern matching
Conference
ISSN
Citations 
PageRank 
2153-0009
9
0.55
References 
Authors
6
4
Name
Order
Citations
PageRank
Andreas Rauch1383.43
Stefan Maier2312.75
Klanner, F.31078.09
Klaus Dietmayer4822102.64