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Traffic Control via Connected and Automated Vehicles: An Open-Road Field Experiment with 100 CAVs
The upper layer is called Speed Planner, and is a centralized optimal control algorithm.
Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed Autonomy Traffic
The Speed Planner comprises two modules: a TSE enhancement module and a target speed design module.
Mesoscale Traffic Forecasting for Real-Time Bottleneck and Shockwave Prediction
Accurate real-time traffic state forecasting plays a pivotal role in traffic control research.
GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving
Deep reinforcement learning (DRL) has been demonstrated to be effective for several complex decision-making applications such as autonomous driving and robotics.
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Learning from demonstrations with SACR2: Soft Actor-Critic with Reward Relabeling
We also present a new method for sparse-reward tasks, based on a reward bonus given to demonstrations and successful episodes.
