Interaction aware trajectory prediction of surrounding vehicles with interaction network and deep ensemble
For the path planning of autonomous vehicles, it is important to predict the future trajectory of
the surrounding vehicles. However, predicting future trajectory is difficult because it needs to …
the surrounding vehicles. However, predicting future trajectory is difficult because it needs to …
Interacting vehicle trajectory prediction with convolutional recurrent neural networks
S Mukherjee, S Wang, A Wallace - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Anticipating the future trajectories of surrounding vehicles is a crucial and challenging task
in path planning for autonomy. We propose a novel Convolutional Long Short Term Memory …
in path planning for autonomy. We propose a novel Convolutional Long Short Term Memory …
Interaction-aware trajectory prediction of connected vehicles using CNN-LSTM networks
Predicting the future trajectory of a surrounding vehicle in congested traffic is one of the
necessary abilities of an autonomous vehicle. In congestion, a vehicle's future movement is …
necessary abilities of an autonomous vehicle. In congestion, a vehicle's future movement is …
Scale-net: Scalable vehicle trajectory prediction network under random number of interacting vehicles via edge-enhanced graph convolutional neural network
Predicting the future trajectory of surrounding vehicles in a randomly varying traffic level is
one of the most challenging problems in developing an autonomous vehicle. Since there is …
one of the most challenging problems in developing an autonomous vehicle. Since there is …
Recup net: Recursive prediction network for surrounding vehicle trajectory prediction with future trajectory feedback
In order to predict the behavior of human drivers accurately, the autonomous vehicle should
be able to understand the reasoning and decision process of motion generation of human …
be able to understand the reasoning and decision process of motion generation of human …
Gisnet: Graph-based information sharing network for vehicle trajectory prediction
The trajectory prediction is a critical and challenging problem in the design of an
autonomous driving system. Many AI-oriented companies, such as Google Waymo, Uber …
autonomous driving system. Many AI-oriented companies, such as Google Waymo, Uber …
TrajectoFormer: Transformer-Based Trajectory Prediction of Autonomous Vehicles with Spatio-temporal Neighborhood Considerations
F Amin, K Gharami, B Sen - International Journal of Computational …, 2024 - Springer
Accurate trajectory prediction of autonomous vehicles is crucial for ensuring road safety.
Predicting precise and accurate trajectories is still considered a challenging problem …
Predicting precise and accurate trajectories is still considered a challenging problem …
Dynamic Spatio-temporal Graph Neural Network for Surrounding-aware Trajectory Prediction of Autonomous Vehicles
H Sadid, C Antoniou - IEEE Transactions on Intelligent Vehicles, 2024 - ieeexplore.ieee.org
Trajectory prediction is a critical aspect of understanding and estimating the motion of
dynamic systems, including robotics and autonomous vehicles (AVs). For safe and efficient …
dynamic systems, including robotics and autonomous vehicles (AVs). For safe and efficient …
Deep learning-based interaction-aware trajectory prediction for autonomous vehicles
X Mo - 2022 - dr.ntu.edu.sg
Predicting future trajectories of surrounding agents and conducting motion planning based
on interaction predictions are of great importance for ensuring the safety and efficiency of …
on interaction predictions are of great importance for ensuring the safety and efficiency of …
Attention based graph convolutional networks for trajectory prediction
Predicting the future trajectory of different traffic agents in the complex traffic environments
plays an important role in keeping the driving safety of self-driving cars, especially on urban …
plays an important role in keeping the driving safety of self-driving cars, especially on urban …
相关搜索
- surrounding vehicles deep ensemble
- surrounding vehicles trajectory prediction
- surrounding vehicles interaction network
- trajectory prediction deep ensemble
- interaction network deep ensemble
- trajectory prediction interaction network
- trajectory prediction for autonomous driving
- trajectory prediction temporal graph
- trajectory prediction cnn lstm
- internet of vehicles attention network
- autonomous driving temporal graph
- trajectory prediction for autonomous vehicles
- trajectory prediction connected vehicles
- trajectory feedback prediction network