Human motion trajectory prediction: A survey
With growing numbers of intelligent autonomous systems in human environments, the ability
of such systems to perceive, understand, and anticipate human behavior becomes …
of such systems to perceive, understand, and anticipate human behavior becomes …
[HTML][HTML] A comprehensive survey on the application of deep and reinforcement learning approaches in autonomous driving
Abstract Recent advances in Intelligent Transport Systems (ITS) and Artificial Intelligence
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
(AI) have stimulated and paved the way toward the widespread introduction of Autonomous …
Tnt: Target-driven trajectory prediction
Predicting the future behavior of moving agents is essential for real world applications. It is
challenging as the intent of the agent and the corresponding behavior is unknown and …
challenging as the intent of the agent and the corresponding behavior is unknown and …
It is not the journey but the destination: Endpoint conditioned trajectory prediction
Human trajectory forecasting with multiple socially interacting agents is of critical importance
for autonomous navigation in human environments, eg, for self-driving cars and social …
for autonomous navigation in human environments, eg, for self-driving cars and social …
Pie: A large-scale dataset and models for pedestrian intention estimation and trajectory prediction
Pedestrian behavior anticipation is a key challenge in the design of assistive and
autonomous driving systems suitable for urban environments. An intelligent system should …
autonomous driving systems suitable for urban environments. An intelligent system should …
Learning to predict vehicle trajectories with model-based planning
Predicting the future trajectories of on-road vehicles is critical for autonomous driving. In this
paper, we introduce a novel prediction framework called PRIME, which stands for Prediction …
paper, we introduce a novel prediction framework called PRIME, which stands for Prediction …
Review of pedestrian trajectory prediction methods: Comparing deep learning and knowledge-based approaches
R Korbmacher, A Tordeux - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
In crowd scenarios, predicting trajectories of pedestrians is a complex and challenging task
depending on many external factors. The topology of the scene and the interactions …
depending on many external factors. The topology of the scene and the interactions …
State estimation and motion prediction of vehicles and vulnerable road users for cooperative autonomous driving: A survey
The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …
increasingly widespread testing of fully autonomous vehicles on public roads, where …
Bitrap: Bi-directional pedestrian trajectory prediction with multi-modal goal estimation
Pedestrian trajectory prediction is an essential task in robotic applications such as
autonomous driving and robot navigation. State-of-the-art trajectory predictors use a …
autonomous driving and robot navigation. State-of-the-art trajectory predictors use a …
Pedestrian trajectory prediction in pedestrian-vehicle mixed environments: A systematic review
M Golchoubian, M Ghafurian… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Planning an autonomous vehicle's (AV) path in a space shared with pedestrians requires
reasoning about pedestrians' future trajectories. A practical pedestrian trajectory prediction …
reasoning about pedestrians' future trajectories. A practical pedestrian trajectory prediction …