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Titel:

A machine learning based biased-sampling approach for planning safe trajectories in complex, dynamic traffic-scenarios

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Amit Chaulwar, Michael Botsch, Wolfgang Utschick
Abstract:
Many variants of the Rapidly-exploring Random Tree (RRT) algorithm use biased-sampling strategies for solving computationally intensive tasks. One of such tasks is the planning of safe trajectories with the simultaneous intervention in both the longitudinal and the lateral dynamics of the vehicle in complex traffic-scenarios with multiple static and dynamic objects. A recently proposed hybrid statistical learning approach uses a 3D convolutional neural network (3D-ConvNet) to predict suitable lo...     »
Kongress- / Buchtitel:
IEEE Intelligent Vehicles Symposium
Jahr:
2017
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