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Found 8 papers, 1 papers with code
OnSiteVRU: A High-Resolution Trajectory Dataset for High-Density Vulnerable Road Users
With the acceleration of urbanization and the growth of transportation demands, the safety of vulnerable road users (VRUs, such as pedestrians and cyclists) in mixed traffic flows has become increasingly prominent, necessitating high-precision and diverse trajectory data to support the development and optimization of autonomous driving systems.
TeLL-Drive: Enhancing Autonomous Driving with Teacher LLM-Guided Deep Reinforcement Learning
To address these limitations, we propose TeLL-Drive, a hybrid framework that integrates a Teacher LLM to guide an attention-based Student DRL policy.
Towards Interactive and Learnable Cooperative Driving Automation: a Large Language Model-Driven Decision-Making Framework
At present, Connected Autonomous Vehicles (CAVs) have begun to open road testing around the world, but their safety and efficiency performance in complex scenarios is still not satisfactory.
Application of Data-Driven Model Predictive Control for Autonomous Vehicle Steering
With the development of autonomous driving technology, there are increasing demands for vehicle control, and MPC has become a widely researched topic in both industry and academia.
Decision Making for Connected Automated Vehicles at Urban Intersections Considering Social and Individual Benefits
To address the coordination issue of connected automated vehicles (CAVs) at urban scenarios, a game-theoretic decision-making framework is proposed that can advance social benefits, including the traffic system efficiency and safety, as well as the benefits of individual users.
Driving Conflict Resolution of Autonomous Vehicles at Unsignalized Intersections: A Differential Game Approach
To realize human-like driving and personalized decision-making, driving aggressiveness is first defined for AVs.
Decision Making of Connected Automated Vehicles at An Unsignalized Roundabout Considering Personalized Driving Behaviours
To improve the safety and efficiency of the intelligent transportation system, particularly in complex urban scenarios, in this paper a game theoretic decision-making framework is designed for connected automated vehicles (CAVs) at unsignalized roundabouts considering their personalized driving behaviours.
Deep Convolutional Neural Network-based Bernoulli Heatmap for Head Pose Estimation
This paper proposes a novel Bernoulli heatmap for head pose estimation from a single RGB image.
