Spatio-Temporal Image Representation and Deep-Learning-Based Decision Framework for Automated Vehicles

Author:

Cheng Shuo1ORCID,Yang Bo1ORCID,Wang Zheng1ORCID,Nakano Kimihiko1ORCID

Affiliation:

1. Institute of Industrial Science, The University of Tokyo, Tokyo, Japan

Funder

Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowship

Grant-in-Aid for Early-Career Scientists

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Reference36 articles.

1. Explaining how a deep neural network trained with end-to-end learning steers a car;bojarski;arXiv 1704 07911,2017

2. Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach

3. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving

4. End to end learning for self-driving cars;bojarski;arXiv 1604 07316 [cs],2016

5. Microscopic Traffic Simulation using SUMO

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