The correct handling of complex traffic-light-controlled intersections is still a challenge for automated vehicles. While a number of image-based approaches tackle close-range recognitions, an early traffic light detection at high distances is of great importance in the area of energy-efficient driving. For this reason, a traffic light detection system consisting of multiple on-board cameras is presented in this work, enabling the detection of traffic lights even from a distance of more than 200m. Furthermore, the presented system is based on tracking techniques using a Labeled Multi-Bernoulli filter in combination with the fusion of classifications based on the Dempster-Shafer theory of evidence. The system was tested on a real world data set collected in Germany and an increase in performance was demonstrated by a multi-camera approach.
Multi-camera traffic light recognition using a classifying Labeled Multi-Bernoulli filter
2017 IEEE Intelligent Vehicles Symposium (IV) ; 1045-1051
2017-06-01
306580 byte
Conference paper
Electronic Resource
English
Multi-Camera Traffic Light Recognition Using a Classifying Labeled Multi-Bernoulli Filter
British Library Conference Proceedings | 2017
|Interaction-Aware Labeled Multi-Bernoulli Filter
IEEE | 2023
|A Fast Implementation of the Labeled Multi-Bernoulli Filter Using Gibbs Sampling
British Library Conference Proceedings | 2017
|