NeuroTrajectory: A Neuroevolutionary Approach to Local State Trajectory Learning for Autonomous Vehicles

Autonomous vehicles are controlled today either based on sequences of decoupled perception-planning-action operations, either based on End2End or deep reinforcement learning (DRL) systems. Current deep learning solutions for autonomous driving are subject to several limitations (e.g., they estimate...

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Bibliographic Details
Published in:	IEEE robotics and automation letters Vol. 4; no. 4; pp. 3441 - 3448
Main Authors:	Grigorescu, Sorin Mihai, Trasnea, Bogdan, Marina, Liviu, Vasilcoi, Andrei, Cocias, Tiberiu
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.10.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Actuators Artificial neural networks Autonomous vehicles Back propagation Estimation Fitness Genetic algorithms Machine learning Mapping Motion control Neural networks Perception Pipelines Sequences Task analysis Training Trajectories Trajectory
ISSN:	2377-3766, 2377-3766
Online Access:	Get full text
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