Social nce: Contrastive learning of socially-aware motion representations
Learning socially-aware motion representations is at the core of recent advances in multi-
agent problems, such as human motion forecasting and robot navigation in crowds. Despite …
agent problems, such as human motion forecasting and robot navigation in crowds. Despite …
Vehicle trajectory prediction works, but not everywhere
Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the
industry and research communities have acknowledged the need for such a pillar by …
industry and research communities have acknowledged the need for such a pillar by …
Trajectory prediction for autonomous driving based on multi-head attention with joint agent-map representation
Predicting the trajectories of surrounding agents is an essential ability for autonomous
vehicles navigating through complex traffic scenes. The future trajectories of agents can be …
vehicles navigating through complex traffic scenes. The future trajectories of agents can be …
[HTML][HTML] Injecting knowledge in data-driven vehicle trajectory predictors
Vehicle trajectory prediction tasks have been commonly tackled from two distinct
perspectives: either with knowledge-driven methods or more recently with data-driven ones …
perspectives: either with knowledge-driven methods or more recently with data-driven ones …
Trajgen: Generating realistic and diverse trajectories with reactive and feasible agent behaviors for autonomous driving
Q Zhang, Y Gao, Y Zhang, Y Guo… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Realistic and diverse simulation scenarios with reactive and feasible agent behaviors can
be used for validation and verification of self-driving system performance without relying on …
be used for validation and verification of self-driving system performance without relying on …
Trajectory prediction in autonomous driving with a lane heading auxiliary loss
Predicting a vehicle's trajectory is an essential ability for autonomous vehicles navigating
through complex urban traffic scenes. Bird's-eye-view roadmap information provides …
through complex urban traffic scenes. Bird's-eye-view roadmap information provides …
Diverse multiple trajectory prediction using a two-stage prediction network trained with lane loss
Prior studies in the field of motion predictions for autonomous driving tend to focus on finding
a trajectory that is close to the ground truth trajectory, which is highly biased toward straight …
a trajectory that is close to the ground truth trajectory, which is highly biased toward straight …
Knowledge augmented machine learning with applications in autonomous driving: A survey
The availability of representative datasets is an essential prerequisite for many successful
artificial intelligence and machine learning models. However, in real life applications these …
artificial intelligence and machine learning models. However, in real life applications these …
A cognition‐inspired trajectory prediction method for vehicles in interactive scenarios
S Xie, J Li, J Wang - IET Intelligent Transport Systems, 2023 - Wiley Online Library
Trajectory prediction of the ego vehicle is necessary for the cooperation driving of intelligent
vehicles and drivers. Methods based on deep learning can fit complex functions, but they …
vehicles and drivers. Methods based on deep learning can fit complex functions, but they …
Improving movement predictions of traffic actors in bird's-eye view models using GANs and differentiable trajectory rasterization
One of the most critical pieces of the self-driving puzzle is the task of predicting future
movement of surrounding traffic actors, which allows the autonomous vehicle to safely and …
movement of surrounding traffic actors, which allows the autonomous vehicle to safely and …