Search Results for author:
Found 8 papers, 6 papers with code
A Preprocessing and Evaluation Toolbox for Trajectory Prediction Research on the Drone Datasets
The availability of high-quality datasets is crucial for the development of behavior prediction algorithms in autonomous vehicles.
Diffusion-Based Environment-Aware Trajectory Prediction
The ability to predict the future trajectories of traffic participants is crucial for the safe and efficient operation of autonomous vehicles.
Uncertainties in Robust Planning and Control of Autonomous Tractor-Trailer Vehicles
To study the effects of uncertainty in autonomous motion planning and control, an 8-DOF model of a tractor-semitrailer is implemented and analyzed.
Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory Prediction
This research investigates the performance of various motion models in combination with numerical solvers for the prediction task.
MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction with Neural ODEs
Enabling resilient autonomous motion planning requires robust predictions of surrounding road users' future behavior.
Interaction-Aware Motion Planning for Autonomous Vehicles with Multi-Modal Obstacle Uncertainty Predictions
This paper proposes an interaction and safety-aware motion-planning method for an autonomous vehicle in uncertain multi-vehicle traffic environments.
Resilient Branching MPC for Multi-Vehicle Traffic Scenarios Using Adversarial Disturbance Sequences
Simulation results from highway driving scenarios show that the proposed method in real-time negotiates traffic situations out of scope for a nominal MPC approach and performs favorably to state-of-the-art reinforcement-learning approaches without requiring prior training.
Vehicle Behavior Prediction and Generalization Using Imbalanced Learning Techniques
The use of learning-based methods for vehicle behavior prediction is a promising research topic.
