Graph-based spatial-temporal convolutional network for vehicle trajectory prediction in autonomous driving

Z Sheng, Y Xu, S Xue, D Li - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …
被引用次数：117 相关文章

Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving

Z Sheng, Y Xu, S Xue, D Li - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …

Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving

Z Sheng, Y Xu, S Xue, D Li - IEEE Transactions on Intelligent …, 2022 - trid.trb.org
Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …

Graph-Based Spatial-Temporal Convolutional Network for Vehicle Trajectory Prediction in Autonomous Driving

Z Sheng, Y Xu, S Xue, D Li - arXiv preprint arXiv:2109.12764, 2021 - arxiv.org
Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …