University of Wisconsin-Madison
Automated Driving, GAN, LSTM, Anomaly Detection
mixed traffic environment, distributed control, deep reinforcement learning, traffic oscillation dampening, connected automated vehicle
Connected Automated Vehicles, Anticipatory Longitudinal Control, Mixed Traffic Environment, Predictive Deep Reinforcement Learning
Mixed Traffic, Car-following, Hybrid Control, Traffic Oscillation Dampening
Keywords: Connected automated vehicles, Deep reinforcement learning, Mixed traffic stream, Signalized intersection, Trajectory optimization.
Anomaly detection, Data-driven, Intelligent Transportation System (ITS), Time Series
End-to-end autonomous driving, Closed-loop simulation, 3D Gaussian Splatting, Controllable testing, Dual-risk matrix, Perception degradation
Vehicle-infrastructure cooperation, Vision Language Model, Semantic scene interpretation, Hierarchical negotiation, Mixed-traffic
Point of Interest, K-means Clustering Algorithm, Latent Dirichlet Allocation, Feature Inference, Intelligent Transportation
Adaptive Takeover Requests Design, Driver Cognitive Modeling, Driver state monitoring, Reaction Time Prediction, Human-in-the-Loop Simulation, Cognitive-Aware Interface Design
Signalized Intersection, Signal Timing Optimization, Traffic Flow Prediction, Mixed-Integer Nonlinear Programming, Cell Transmission Model
Physics enhanced residual learning, Connected and automated vehicles, Centralized platoon control, Online adaptive control
Driver-initiated Intervention, Latent Intention Modeling, Time-to-intervention Prediction, Human-in-the-Loop Simulation, Multi-source State Coupling, Automated Driving
