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Autonomous driving system: A comprehensive survey
Automation is increasingly at the forefront of transportation research, with the potential to
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …
bring fully autonomous vehicles to our roads in the coming years. This comprehensive …
A review of vision-based traffic semantic understanding in ITSs
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …
situations and emergencies more accurately and provide a more accurate basis for anomaly …
Query-centric trajectory prediction
Predicting the future trajectories of surrounding agents is essential for autonomous vehicles
to operate safely. This paper presents QCNet, a modeling framework toward pushing the …
to operate safely. This paper presents QCNet, a modeling framework toward pushing the …
Leapfrog diffusion model for stochastic trajectory prediction
To model the indeterminacy of human behaviors, stochastic trajectory prediction requires a
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …
A survey on trajectory-prediction methods for autonomous driving
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
Motion transformer with global intention localization and local movement refinement
Predicting multimodal future behavior of traffic participants is essential for robotic vehicles to
make safe decisions. Existing works explore to directly predict future trajectories based on …
make safe decisions. Existing works explore to directly predict future trajectories based on …
Hivt: Hierarchical vector transformer for multi-agent motion prediction
Accurately predicting the future motions of surrounding traffic agents is critical for the safety
of autonomous vehicles. Recently, vectorized approaches have dominated the motion …
of autonomous vehicles. Recently, vectorized approaches have dominated the motion …
Eqmotion: Equivariant multi-agent motion prediction with invariant interaction reasoning
Learning to predict agent motions with relationship reasoning is important for many
applications. In motion prediction tasks, maintaining motion equivariance under Euclidean …
applications. In motion prediction tasks, maintaining motion equivariance under Euclidean …
Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying
Motion prediction is crucial for autonomous driving systems to understand complex driving
scenarios and make informed decisions. However, this task is challenging due to the diverse …
scenarios and make informed decisions. However, this task is challenging due to the diverse …
Motiontrack: Learning robust short-term and long-term motions for multi-object tracking
The main challenge of Multi-Object Tracking (MOT) lies in maintaining a continuous
trajectory for each target. Existing methods often learn reliable motion patterns to match the …
trajectory for each target. Existing methods often learn reliable motion patterns to match the …