A Survey of Generative AI for Intelligent Transportation Systems
Intelligent transportation systems play a crucial role in modern traffic management and
optimization, greatly improving traffic efficiency and safety. With the rapid development of …
optimization, greatly improving traffic efficiency and safety. With the rapid development of …
Longitudinal control of automated vehicles: A novel approach by integrating deep reinforcement learning with intelligent driver model
Deep reinforcement learning (DRL) provides a promising approach for the implementation
of autonomous driving. By utilizing a trained DRL model as the longitudinal controller, the …
of autonomous driving. By utilizing a trained DRL model as the longitudinal controller, the …
Modeling of Complex Traffic Interaction Under Uncontrolled Intersection Scenario
J Li, W Deng, Y Wang, J Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Complex traffic scenarios at uncontrolled intersections are crucial for the test validation of
autonomous driving systems. The core of the test scenario construction lies in the accurate …
autonomous driving systems. The core of the test scenario construction lies in the accurate …
Structured Graph Network for Constrained Robot Crowd Navigation with Low Fidelity Simulation
We investigate the feasibility of deploying reinforcement learning (RL) policies for
constrained crowd navigation using a low-fidelity simulator. We introduce a representation of …
constrained crowd navigation using a low-fidelity simulator. We introduce a representation of …
A Gentle Introduction and Tutorial on Deep Generative Models in Transportation Research
Deep Generative Models (DGMs) have rapidly advanced in recent years, becoming
essential tools in various fields due to their ability to learn complex data distributions and …
essential tools in various fields due to their ability to learn complex data distributions and …