2,171 research outputs found
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 increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling
Vehicle trajectory prediction is crucial for autonomous driving and advanced
driver assistant systems. While existing approaches may sample from a predicted
distribution of vehicle trajectories, they lack the ability to explore it -- a
key ability for evaluating safety from a planning and verification perspective.
In this work, we devise a novel approach for generating realistic and diverse
vehicle trajectories. We extend the generative adversarial network (GAN)
framework with a low-dimensional approximate semantic space, and shape that
space to capture semantics such as merging and turning. We sample from this
space in a way that mimics the predicted distribution, but allows us to control
coverage of semantically distinct outcomes. We validate our approach on a
publicly available dataset and show results that achieve state-of-the-art
prediction performance, while providing improved coverage of the space of
predicted trajectory semantics.Comment: 8 pages, 5 figures, 1 tabl
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