A survey of deep learning applications to autonomous vehicle control
Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …
in all driving scenarios is challenging due to the highly complex environment and inability to …
[HTML][HTML] A comprehensive survey on the application of deep and reinforcement learning approaches in autonomous driving
Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
A survey of deep learning techniques for autonomous driving
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …
A review of motion planning algorithms for intelligent robots
Principles of typical motion planning algorithms are investigated and analyzed in this paper.
These algorithms include traditional planning algorithms, classical machine learning …
These algorithms include traditional planning algorithms, classical machine learning …
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
A survey of deep RL and IL for autonomous driving policy learning
Z Zhu, H Zhao - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
Autonomous driving (AD) agents generate driving policies based on online perception
results, which are obtained at multiple levels of abstraction, eg, behavior planning, motion …
results, which are obtained at multiple levels of abstraction, eg, behavior planning, motion …
Automated driving in uncertain environments: Planning with interaction and uncertain maneuver prediction
Automated driving requires decision making in dynamic and uncertain environments. The
uncertainty from the prediction originates from the noisy sensor data and from the fact that …
uncertainty from the prediction originates from the noisy sensor data and from the fact that …
Deep reinforcement learning in transportation research: A review
Applying and adapting deep reinforcement learning (DRL) to tackle transportation problems
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …
Recent trends in task and motion planning for robotics: A survey
Autonomous robots are increasingly served in real-world unstructured human environments
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …
Reward (mis) design for autonomous driving
This article considers the problem of diagnosing certain common errors in reward design. Its
insights are also applicable to the design of cost functions and performance metrics more …
insights are also applicable to the design of cost functions and performance metrics more …