DocumentCode :
3504357
Title :
Video-based trailer detection and articulation estimation
Author :
Caup, Lukas ; Salmen, Jan ; Muharemovic, Ibro ; Houben, Sebastian
Author_Institution :
Inst. for Comput. Neural Sci., Univ. of Bochum, Bochum, Germany
fYear :
2013
fDate :
23-26 June 2013
Firstpage :
1179
Lastpage :
1184
Abstract :
Even for experienced drivers handling a roll trailer with a passenger car is a difficult and often tedious task. Moreover, the driver needs to keep track of the trailer´s driving stability on unsteady roads. There are driver assistance systems that can simplify trajectory planning and observe the oscillation amplitude, but they require additional hardware. In this paper, we present a method for trailer detection and articulation angle measurement based on video data from a rear end wide-angle camera. It consists of two stages: to decide whether or not a trailer is coupled to the vehicle and to estimate its articulation angle. These calculations work on single video frames. The vehicle is therefore not required to be in motion. However, we stabilize the single frame estimations by temporal integration. We perform training and parameter optimization and evaluate the accuracy of our approach by comparing the results to those of an articulation measurement unit attached to a test vehicle´s hitch. Results show that it can very reliably be determined whether or not a trailer is coupled to the vehicle. Furthermore, its articulation can be estimated with a mean error of less than two degrees.
Keywords :
driver information systems; image sensors; learning (artificial intelligence); optimisation; video signal processing; articulation angle measurement; articulation estimation; driver assistance systems; oscillation amplitude; passenger car; rear end wide-angle camera; roll trailer; single frame estimations; temporal integration; trajectory planning; video-based trailer detection; Cameras; Estimation error; Hardware; Prototypes; Training; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location :
Gold Coast, QLD
ISSN :
1931-0587
Print_ISBN :
978-1-4673-2754-1
Type :
conf
DOI :
10.1109/IVS.2013.6629626
Filename :
6629626
Link To Document :
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