Poster 24: D2CAV: Creating a Maneuver-based Driving Dataset and Model based on Recurrent Neural Networks (RNNs) for Autonomous Vehicles
(Room Palms Ballroom)
16 Jul 19
5:30 PM
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7:00 PM
Tracks:
Vehicle Automation Technology
The short-term future of the autonomous driving will be a hybrid scenario where both automated and human-driven vehicles co-exist in the same environment. In order to address the needs of such architecture, many technologies such as connected vehicles and predictive control for automated vehicles have been introduced in the literature. Both aforementioned solutions rely on driving data of the human driver. In this work, we investigate the currently available driving datasets and introduce a real-world maneuver-based driving dataset and a trained model based on recurrent neural networks which can be utilized to parse and label existing benchmarks.