WcDT: World-centric Diffusion Transformer for Traffic Scene Generation
In this paper, we introduce a novel approach for autonomous driving trajectory generation by
harnessing the complementary strengths of diffusion probabilistic models (aka, diffusion …
harnessing the complementary strengths of diffusion probabilistic models (aka, diffusion …
TSDiT: Traffic Scene Diffusion Models With Transformers
C Yang, T Shi - arXiv preprint arXiv:2405.02289, 2023 - arxiv.org
In this paper, we introduce a novel approach to trajectory generation for autonomous driving,
combining the strengths of Diffusion models and Transformers. First, we use the historical …
combining the strengths of Diffusion models and Transformers. First, we use the historical …
Hierarchical vector transformer vehicle trajectories prediction with diffusion convolutional neural networks
In dynamic and interactive autonomous driving scenarios, accurately predicting the future
movements of vehicle agents is crucial. However, current methods often fail to capture …
movements of vehicle agents is crucial. However, current methods often fail to capture …
Trajvae: A variational autoencoder model for trajectory generation
Large-scale trajectory dataset is always required for self-driving and many other
applications. In this paper, we focus on the trajectory generation problem, which aims to …
applications. In this paper, we focus on the trajectory generation problem, which aims to …
Controllable Diverse Sampling for Diffusion Based Motion Behavior Forecasting
In autonomous driving tasks, trajectory prediction in complex traffic environments requires
adherence to real-world context conditions and behavior multimodalities. Existing methods …
adherence to real-world context conditions and behavior multimodalities. Existing methods …
Diff-RNTraj: A Structure-aware Diffusion Model for Road Network-constrained Trajectory Generation
Trajectory data is essential for various applications as it records the movement of vehicles.
However, publicly available trajectory datasets remain limited in scale due to privacy …
However, publicly available trajectory datasets remain limited in scale due to privacy …
Probabilistic Image-Driven Traffic Modeling via Remote Sensing
This work addresses the task of modeling spatiotemporal traffic patterns directly from
overhead imagery, which we refer to as image-driven traffic modeling. We extend this line of …
overhead imagery, which we refer to as image-driven traffic modeling. We extend this line of …
A multi-modal vehicle trajectory prediction framework via conditional diffusion model: A coarse-to-fine approach
Z Li, H Liang, H Wang, X Zheng, J Wang… - Knowledge-Based …, 2023 - Elsevier
Accurate prediction of the future motion of surrounding vehicles is crucial for ensuring the
safety of motion planning in autonomous vehicles. However, it is challenging to perform …
safety of motion planning in autonomous vehicles. However, it is challenging to perform …
Transfer Learning Study of Motion Transformer-based Trajectory Predictions
L Ullrich, A McMaster, K Graichen - arXiv preprint arXiv:2404.08271, 2024 - arxiv.org
Trajectory planning in autonomous driving is highly dependent on predicting the emergent
behavior of other road users. Learning-based methods are currently showing impressive …
behavior of other road users. Learning-based methods are currently showing impressive …
[PDF][PDF] SCTP: Scene Compliant Trajectory Prediction Using Diffusion and Point Clouds
MB Andersen, SA Hansen - projekter.aau.dk
The unpredictable nature of human be-haviour is a critical aspect in the domain of trajectory
prediction, especially when viewed in the context of autonomous vehicles. Generational …
prediction, especially when viewed in the context of autonomous vehicles. Generational …