Intention-aware vehicle trajectory prediction based on spatial-temporal dynamic attention network for internet of vehicles
Vehicle trajectory prediction is a keystone for the application of the internet of vehicles (IoV).
With the help of deep learning and big data, it is possible to understand the between-vehicle …
With the help of deep learning and big data, it is possible to understand the between-vehicle …
Vehicle trajectory prediction based on intention-aware non-autoregressive transformer with multi-attention learning for Internet of Vehicles
X Chen, H Zhang, F Zhao, Y Cai… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As a core function of autonomous driving (AD) and the Internet of Vehicles (IoV), accurately
predicting the trajectory of vehicles can significantly improve traffic safety and reduce crash …
predicting the trajectory of vehicles can significantly improve traffic safety and reduce crash …
Traj-llm: A new exploration for empowering trajectory prediction with pre-trained large language models
Predicting the future trajectories of dynamic traffic actors is a cornerstone task in
autonomous driving. Though existing notable efforts have resulted in impressive …
autonomous driving. Though existing notable efforts have resulted in impressive …
A review on intention-aware and interaction-aware trajectory prediction for autonomous vehicles
This paper presents a literature review on Intention-aware and Interaction-aware Trajectory
Prediction for Autonomous Vehicle, which covers primary studies since 2008. The research …
Prediction for Autonomous Vehicle, which covers primary studies since 2008. The research …
Multi-head attention based probabilistic vehicle trajectory prediction
This paper presents online-capable deep learning model for probabilistic vehicle trajectory
prediction. We propose a simple encoder-decoder architecture based on multihead …
prediction. We propose a simple encoder-decoder architecture based on multihead …
A temporal multi-gate mixture-of-experts approach for vehicle trajectory and driving intention prediction
R Yuan, M Abdel-Aty, Q **ang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate vehicle trajectory prediction is critical for autonomous vehicles and advanced
driver assistance systems to make driving decisions and improve traffic safety. This paper …
driver assistance systems to make driving decisions and improve traffic safety. This paper …
Graph-based interaction-aware multimodal 2D vehicle trajectory prediction using diffusion graph convolutional networks
Predicting vehicle trajectories is crucial to ensuring automated vehicle operation efficiency
and safety, particularly on congested multi-lane highways. In such dynamic environments, a …
and safety, particularly on congested multi-lane highways. In such dynamic environments, a …
VNAGT: Variational non-autoregressive graph transformer network for multi-agent trajectory prediction
Accurately predicting the trajectory of road agents in complex traffic scenarios is challenging
because the movement patterns of agents are complex and stochastic, not only depending …
because the movement patterns of agents are complex and stochastic, not only depending …
A multi-task learning network with a collision-aware graph transformer for traffic-agents trajectory prediction
It is critical for autonomous vehicles to accurately forecast the future trajectories of
surrounding agents to avoid collisions. However, capturing the complex interactions …
surrounding agents to avoid collisions. However, capturing the complex interactions …
A taxonomy and review of algorithms for modeling and predicting human driver behavior
K Brown, K Driggs-Campbell… - arxiv preprint arxiv …, 2020 - arxiv.org
We present a review and taxonomy of 200 models from the literature on driver behavior
modeling. We begin by introducing a mathematical framework for describing the dynamics of …
modeling. We begin by introducing a mathematical framework for describing the dynamics of …