Autonomous driving system: A comprehensive survey

J Zhao, W Zhao, B Deng, Z Wang, F Zhang… - Expert Systems with …, 2024‏ - Elsevier
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 …

A review of vision-based traffic semantic understanding in ITSs

J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
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 …

Query-centric trajectory prediction

Z Zhou, J Wang, YH Li… - Proceedings of the IEEE …, 2023‏ - openaccess.thecvf.com
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 …

Leapfrog diffusion model for stochastic trajectory prediction

W Mao, C Xu, Q Zhu, S Chen… - Proceedings of the IEEE …, 2023‏ - openaccess.thecvf.com
To model the indeterminacy of human behaviors, stochastic trajectory prediction requires a
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …

A survey on trajectory-prediction methods for autonomous driving

Y Huang, J Du, Z Yang, Z Zhou… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
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 …

Motion transformer with global intention localization and local movement refinement

S Shi, L Jiang, D Dai, B Schiele - Advances in Neural …, 2022‏ - proceedings.neurips.cc
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 …

Hivt: Hierarchical vector transformer for multi-agent motion prediction

Z Zhou, L Ye, J Wang, K Wu… - Proceedings of the IEEE …, 2022‏ - openaccess.thecvf.com
Accurately predicting the future motions of surrounding traffic agents is critical for the safety
of autonomous vehicles. Recently, vectorized approaches have dominated the motion …

Eqmotion: Equivariant multi-agent motion prediction with invariant interaction reasoning

C Xu, RT Tan, Y Tan, S Chen… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Learning to predict agent motions with relationship reasoning is important for many
applications. In motion prediction tasks, maintaining motion equivariance under Euclidean …

Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying

S Shi, L Jiang, D Dai, B Schiele - IEEE Transactions on Pattern …, 2024‏ - ieeexplore.ieee.org
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 …

Motiontrack: Learning robust short-term and long-term motions for multi-object tracking

Z Qin, S Zhou, L Wang, J Duan… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
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 …