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Recent advances in reinforcement learning-based autonomous driving behavior planning: A survey
Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
A Spatial–Temporal Predictive Transformer Network for Level-3 Autonomous Vehicle Decision-Making
This study explores the effect of takeover time (TOT) on decision-making for Level-3
autonomous vehicles (L3-AVs). The existing research on L3-AV lacks an in-depth analysis …
autonomous vehicles (L3-AVs). The existing research on L3-AV lacks an in-depth analysis …
Template Reinforcement Learning for Automated Driving with Scenario Switching Inference Labeling
S Lu, B Yang, Z Yang, X Pei - 2023 7th CAA International …, 2023 - ieeexplore.ieee.org
Decision making in dense traffic uncertainty scenarios is challenging for autonomous
vehicles. Compare with costly manually designed driving policy, deep Reinforcement …
vehicles. Compare with costly manually designed driving policy, deep Reinforcement …
Self-learning Decision and Control for Highly Automated Vehicles
The decision and control module plays a key role for autonomous driving, which is
responsible for generating appropriate control commands that navigate the autonomous …
responsible for generating appropriate control commands that navigate the autonomous …
Review of Autonomous Driving in Unexpected Events
Y Chen - 2024 International Conference on Intelligent Robotics …, 2024 - ieeexplore.ieee.org
In the field of autonomous driving, much of the research on decision-making systems
focuses on predictable data. This paper emphasizes unpredictable data and behaviors …
focuses on predictable data. This paper emphasizes unpredictable data and behaviors …