In this paper, we propose a real-time vision-based filtering algorithm for steering angle estimation in autonomous driving. A novel scene-based particle filtering algorithm is used to estimate and track the steering angle using images obtained from a monocular camera. Highly accurate proposal distributions and likelihood are modeled for the second order particle filter, at the scene-level, using deep learning. For every road scene, an individual proposal distribution and likelihood model is learnt for the corresponding particle filter. The proposal distribution is modeled using a novel long short term memory network-mixture-of-expert-based regression framework. To facilitate the learning of highly accurate proposal distributions, each road scene is partitioned into straight driving, left turning and right turning sub-partitions. Subsequently, each expert in the regression framework accurately model the expert driver's behavior within a specific partition of the given road scene. Owing to the accuracy of the modelled proposal distributions, the steering angle is robustly tracked, even with a limited number of sampled particles. The sampled particles are assigned importance weights using a deep learning-based likelihood. The likelihood is modeled with a convolutional neural network and extra trees-based regression framework, which predicts the steering angle for a given image. We validate our proposed algorithm using multiple sequences. We perform a detailed parameter analysis and a comparative analysis of our proposed algorithm with different baseline algorithms. Experimental results show that the proposed algorithm can robustly track the steering angles with few particles in real-time even for challenging scenes.
Automated driving by monocular camera using deep mixture of experts
01.06.2017
1837908 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Automated Driving by Monocular Camera Using Deep Mixture of Experts
British Library Conference Proceedings | 2017
|Autonomous Driving Monocular Camera Calibration Based on Camera Raw Data Injection
British Library Conference Proceedings | 2022
|Autonomous Driving Monocular Camera Calibration Based on Camera Raw Data Injection
SAE Technical Papers | 2022
|DIRTY MONOCULAR CAMERA DETECTION METHODS FOR AUTONOMOUS DRIVING VEHICLE
Europäisches Patentamt | 2021
|