Behavioral intention prediction in driving scenes: A survey
In driving scenes, road agents often engage in frequent interaction and strive to understand
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …
their surroundings. Ego-agent (each road agent itself) predicts what behavior will be …
Rethinking integration of prediction and planning in deep learning-based automated driving systems: a review
Automated driving has the potential to revolutionize personal, public, and freight mobility.
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Besides the enormous challenge of perception, ie accurately perceiving the environment …
Planning-inspired hierarchical trajectory prediction via lateral-longitudinal decomposition for autonomous driving
Trajectory prediction plays a crucial role in bridging the gap between perception and
planning in autonomous driving systems. However, most existing methods perform motion …
planning in autonomous driving systems. However, most existing methods perform motion …
A Hierarchical Intention Inference Model for Connected and Automated Vehicles
Z Li, Y Wang, Z Zuo, C Hu - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Lane-changing is one of the typical maneuvers with high risk, which can cause
uncomfortable brake and dangerous crash. An experienced human driver keeps an eye on …
uncomfortable brake and dangerous crash. An experienced human driver keeps an eye on …
Social Force Embedded Mixed Graph Convolutional Network for Multi-class Trajectory Prediction
Q Du, X Wang, S Yin, L Li, H Ning - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Accurate prediction of agent motion trajectories is crucial for autonomous driving,
contributing to the reduction of collision risks in human-vehicle interactions and ensuring …
contributing to the reduction of collision risks in human-vehicle interactions and ensuring …
Domain Adaptation for Enhanced Object Detection in Foggy and Rainy Weather for Autonomous Driving
Most object detection models for autonomous driving may experience a significant drop in
performance when deployed in real-world applications, due to the well-known domain shift …
performance when deployed in real-world applications, due to the well-known domain shift …
SocialFormer: Social Interaction Modeling with Edge-enhanced Heterogeneous Graph Transformers for Trajectory Prediction
Accurate trajectory prediction is crucial for ensuring safe and efficient autonomous driving.
However, most existing methods overlook complex interactions between traffic participants …
However, most existing methods overlook complex interactions between traffic participants …