A comprehensive survey on multi-agent reinforcement learning for connected and automated vehicles
Connected and automated vehicles (CAVs) require multiple tasks in their seamless
maneuverings. Some essential tasks that require simultaneous management and actions …
maneuverings. Some essential tasks that require simultaneous management and actions …
Causal-based time series domain generalization for vehicle intention prediction
Accurately predicting the possible behaviors of traffic participants is an essential capability
for autonomous vehicles. Since autonomous vehicles need to navigate in dynamically …
for autonomous vehicles. Since autonomous vehicles need to navigate in dynamically …
Prediction failure risk-aware decision-making for autonomous vehicles on signalized intersections
Motion prediction modules are crucial for autonomous vehicles to forecast the future
behavior of surrounding road users. Failures in prediction modules can mislead a …
behavior of surrounding road users. Failures in prediction modules can mislead a …
Continual multi-agent interaction behavior prediction with conditional generative memory
Multi-agent trajectory prediction plays a crucial role in robotics and autonomous driving. The
current mainstream research focuses on how to achieve accurate prediction on one large …
current mainstream research focuses on how to achieve accurate prediction on one large …
Video action recognition for lane-change classification and prediction of surrounding vehicles
M Biparva, D Fernández-Llorca… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
In highway scenarios, an alert human driver will typically anticipate early cut-in/cut-out
maneuvers of surrounding vehicles using visual cues mainly. Autonomous vehicles must …
maneuvers of surrounding vehicles using visual cues mainly. Autonomous vehicles must …
Deep learning for vision-based prediction: A survey
A Rasouli - arXiv preprint arXiv:2007.00095, 2020 - arxiv.org
Vision-based prediction algorithms have a wide range of applications including autonomous
driving, surveillance, human-robot interaction, weather prediction. The objective of this …
driving, surveillance, human-robot interaction, weather prediction. The objective of this …
The AD4CHE dataset and its application in typical congestion Scenarios of Traffic Jam Pilot Systems
Autonomous driving has attracted considerable attention from research and industry
communities. Although prototypes of automated vehicles (AVs) are developed, remaining …
communities. Although prototypes of automated vehicles (AVs) are developed, remaining …
Analyzing the suitability of cost functions for explaining and imitating human driving behavior based on inverse reinforcement learning
Autonomous vehicles are sharing the road with human drivers. In order to facilitate
interactive driving and cooperative behavior in dense traffic, a thorough understanding and …
interactive driving and cooperative behavior in dense traffic, a thorough understanding and …
A review on action recognition for accident detection in smart city transportation systems
Accident detection and public traffic safety is a crucial aspect of safe and better community.
Monitoring traffic flow in smart cities using different surveillance cameras plays a crucial role …
Monitoring traffic flow in smart cities using different surveillance cameras plays a crucial role …
Multi-modal interaction-aware motion prediction at unsignalized intersections
Autonomous vehicle technologies have evolved quickly over the last few years, with safety
being one of the key requirements for their full deployment. However, ensuring their safety …
being one of the key requirements for their full deployment. However, ensuring their safety …