Holistic network virtualization and pervasive network intelligence for 6G
In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …
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 …
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 …
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 …
Multimodal motion prediction with stacked transformers
Predicting multiple plausible future trajectories of the nearby vehicles is crucial for the safety
of autonomous driving. Recent motion prediction approaches attempt to achieve such …
of autonomous driving. Recent motion prediction approaches attempt to achieve such …
Prediction-uncertainty-aware decision-making for autonomous vehicles
Motion prediction is the fundamental input for decision-making in autonomous vehicles. The
current motion prediction solutions are designed with a strong reliance on black box …
current motion prediction solutions are designed with a strong reliance on black box …
Multi-agent trajectory prediction with heterogeneous edge-enhanced graph attention network
Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential
for safe and efficient operation of connected automated vehicles under complex driving …
for safe and efficient operation of connected automated vehicles under complex driving …
Lidar for autonomous driving: The principles, challenges, and trends for automotive lidar and perception systems
Y Li, J Ibanez-Guzman - IEEE Signal Processing Magazine, 2020 - ieeexplore.ieee.org
Autonomous vehicles rely on their perception systems to acquire information about their
immediate surroundings. It is necessary to detect the presence of other vehicles …
immediate surroundings. It is necessary to detect the presence of other vehicles …
Groupnet: Multiscale hypergraph neural networks for trajectory prediction with relational reasoning
Demystifying the interactions among multiple agents from their past trajectories is
fundamental to precise and interpretable trajectory prediction. However, previous works only …
fundamental to precise and interpretable trajectory prediction. However, previous works only …