50 citations · 60 across the 11 of their papers we have counts for
11 papers
Vessel Trajectory Prediction using COLREGs-aware Optimal Planning
David Kaikkonen, Fredrik Ljungberg, Erik Frisk
This paper presents a trajectory prediction method for marine vessels based on optimal planning. Crude initial trajectories respecting static obstacles are first generated using A*…
Unveiling Transferability in Trajectory Prediction via Latent Scene Embeddings
Theodor Westny, David Axelsson, Björn Olofsson +1
The growing availability of trajectory datasets has fueled major advances in data-driven motion prediction. Yet, models trained on one dataset often fail to generalize beyond their…
Behavior-Aware Online Prediction of Obstacle Occupancy using Zonotopes
Alvaro Carrizosa-Rendon, Jian Zhou, Erik Frisk +2
Predicting the motion of surrounding vehicles is key to safe autonomous driving, especially in unstructured environments without prior information. This paper proposes a novel onli…
Uncertainty-Aware Decision-Making and Planning for Autonomous Forced Merging
Jian Zhou, Yulong Gao, Björn Olofsson +1
In this paper, we develop an uncertainty-aware decision-making and motion-planning method for an autonomous ego vehicle in forced merging scenarios, considering the motion uncertai…
Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets
Theodor Westny, Björn Olofsson, Erik Frisk
The availability of high-quality datasets is crucial for the development of behavior prediction algorithms in autonomous vehicles. This paper highlights the need to standardize the…
Observer-Based Environment Robust Control Barrier Functions for Safety-critical Control with Dynamic Obstacles
Ying Shuai Quan, Jian Zhou, Erik Frisk +1
This paper proposes a safety-critical controller for dynamic and uncertain environments, leveraging a robust environment control barrier function (ECBF) to enhance the robustness a…
Diffusion-Based Environment-Aware Trajectory Prediction
Theodor Westny, Björn Olofsson, Erik Frisk
The ability to predict the future trajectories of traffic participants is crucial for the safe and efficient operation of autonomous vehicles. In this paper, a diffusion-based gene…
Robust Predictive Motion Planning by Learning Obstacle Uncertainty
Jian Zhou, Yulong Gao, Ola Johansson +2
Safe motion planning for robotic systems in dynamic environments is nontrivial in the presence of uncertain obstacles, where estimation of obstacle uncertainties is crucial in pred…
Uncertainties in Robust Planning and Control of Autonomous Tractor-Trailer Vehicles
Theodor Westny, Björn Olofsson, Erik Frisk
To study the effects of uncertainty in autonomous motion planning and control, an 8-DOF model of a tractor-semitrailer is implemented and analyzed. The implications of uncertaintie…
Stability-Informed Initialization of Neural Ordinary Differential Equations
Theodor Westny, Arman Mohammadi, Daniel Jung +1
This paper addresses the training of Neural Ordinary Differential Equations (neural ODEs), and in particular explores the interplay between numerical integration techniques, stabil…
Interaction-Aware Motion Planning for Autonomous Vehicles with Multi-Modal Obstacle Uncertainty Predictions
Jian Zhou, Björn Olofsson, Erik Frisk
This paper proposes an interaction and safety-aware motion-planning method for an autonomous vehicle in uncertain multi-vehicle traffic environments. The method integrates the abil…