Conditional goal-oriented trajectory prediction for interacting vehicles with vectorized representation
This paper aims to tackle the interactive behavior prediction task, and proposes a novel
Conditional Goal-oriented Trajectory Prediction (CGTP) framework to jointly generate scene …
Conditional Goal-oriented Trajectory Prediction (CGTP) framework to jointly generate scene …
Conditional Goal-Oriented Trajectory Prediction for Interacting Vehicles
Predicting future trajectories of pairwise traffic agents in highly interactive scenarios, such as
cut-in, yielding, and merging, is challenging for autonomous driving. The existing works …
cut-in, yielding, and merging, is challenging for autonomous driving. The existing works …
EFIN-MP: Explicit Future Interaction Network for Motion Prediction
L Li, J Su, L Qiu, J Lian, G Guo - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Accurate prediction the future movements of surrounding traffic participants is crucial for
autonomous driving. Among various strategies, learning complex interactive behaviors …
autonomous driving. Among various strategies, learning complex interactive behaviors …
Goal-Guided and Interaction-Aware State Refinement Graph Attention Network for Multi-Agent Trajectory Prediction
Multi-agent trajectory prediction plays a pivotal role for intelligent transportation and
autonomous driving. Modeling the social interaction among agents and revealing the …
autonomous driving. Modeling the social interaction among agents and revealing the …
Social-wagdat: Interaction-aware trajectory prediction via wasserstein graph double-attention network
Effective understanding of the environment and accurate trajectory prediction of surrounding
dynamic obstacles are indispensable for intelligent mobile systems (like autonomous …
dynamic obstacles are indispensable for intelligent mobile systems (like autonomous …
ProspectNet: Weighted conditional attention for future interaction modeling in behavior prediction
Y Pang, Z Guo, B Zhuang - arXiv preprint arXiv:2208.13848, 2022 - arxiv.org
Behavior prediction plays an important role in integrated autonomous driving software
solutions. In behavior prediction research, interactive behavior prediction is a less-explored …
solutions. In behavior prediction research, interactive behavior prediction is a less-explored …
Domain knowledge driven pseudo labels for interpretable goal-conditioned interactive trajectory prediction
Motion forecasting in highly interactive scenarios is a challenging problem in autonomous
driving. In such scenarios, we need to accurately predict the joint behavior of interacting …
driving. In such scenarios, we need to accurately predict the joint behavior of interacting …
GAP: Goal-aware prediction with hierarchical interactive representation for vehicle trajectory
Predicting the future trajectories of surrounding vehicles plays a vital role in ensuring the
safety of autonomous driving. It is extremely challenging for the pure imitation method due to …
safety of autonomous driving. It is extremely challenging for the pure imitation method due to …
MFAN: Mixing Feature Attention Network for trajectory prediction
Accurate trajectory prediction of surrounding agents is essential for autonomous vehicles,
where the key challenge is to understand the complex interactions among agents. Previous …
where the key challenge is to understand the complex interactions among agents. Previous …
Spatio-temporal graph dual-attention network for multi-agent prediction and tracking
An effective understanding of the environment and accurate trajectory prediction of
surrounding dynamic obstacles are indispensable for intelligent mobile systems (eg …
surrounding dynamic obstacles are indispensable for intelligent mobile systems (eg …