Periodic event-triggered fault detection for safe platooning control of intelligent and connected vehicles
Fault detection is not only a useful approach to guarantee the safety of a vehicle platooning
system but also an indispensable part of functional safety for future connected automated …
system but also an indispensable part of functional safety for future connected automated …
VNAGT: Variational non-autoregressive graph transformer network for multi-agent trajectory prediction
X Chen, H Zhang, Y Hu, J Liang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurately predicting the trajectory of road agents in complex traffic scenarios is challenging
because the movement patterns of agents are complex and stochastic, not only depending …
because the movement patterns of agents are complex and stochastic, not only depending …
Kinematics-aware multigraph attention network with residual learning for heterogeneous trajectory prediction
Trajectory prediction for heterogeneous traffic agents plays a crucial role in ensuring the
safety and efficiency of automated driving in highly interactive traffic environments …
safety and efficiency of automated driving in highly interactive traffic environments …
A review of hybrid physics-based machine learning approaches in traffic state estimation
Traffic state estimation (TSE) plays a significant role in traffic control and operations since it
can provide accurate and high-resolution traffic estimations for locations without traffic states …
can provide accurate and high-resolution traffic estimations for locations without traffic states …
A Review of Deep Learning-Based Vehicle Motion Prediction for Autonomous Driving
Autonomous driving vehicles can effectively improve traffic conditions and promote the
development of intelligent transportation systems. An autonomous vehicle can be divided …
development of intelligent transportation systems. An autonomous vehicle can be divided …
Vehicle sideslip trajectory prediction based on time-series analysis and multi-physical model fusion
L Cao, Y Luo, Y Wang, J Chen… - Journal of Intelligent and …, 2023 - ieeexplore.ieee.org
On highways, vehicles that swerve out of their lane due to sideslip can pose a serious threat
to the safety of autonomous vehicles. To ensure their safety, predicting the sideslip …
to the safety of autonomous vehicles. To ensure their safety, predicting the sideslip …
Vehicle Interactive Dynamic Graph Neural Network Based Trajectory Prediction for Internet of Vehicles
In the context of the booming Internet of Vehicles, predicting vehicle trajectories is crucial for
intelligent transportation systems. Existing methods, reliant on sensor data and behavior …
intelligent transportation systems. Existing methods, reliant on sensor data and behavior …
Graph representation learning in the ITS: Car-following informed spatiotemporal network for vehicle trajectory predictions
YH Yin, X Lü, SK Li, LX Yang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Multimodal synchronization has become the research highlight of the ITS, where complex
driving scenarios, various types of vehicles and diverse data sources are crucial …
driving scenarios, various types of vehicles and diverse data sources are crucial …
Network macroscopic fundamental diagram-informed graph learning for traffic state imputation
Traffic state imputation refers to the estimation of missing values of traffic variables, such as
flow rate and traffic density, using available data. It furnishes comprehensive traffic context …
flow rate and traffic density, using available data. It furnishes comprehensive traffic context …
Safety aware neural network for connected and automated vehicle operations
Contemporary research in connected and automated vehicle (CAV) operations typically
segregates trajectory prediction from planning in two segregated models. Trajectory …
segregates trajectory prediction from planning in two segregated models. Trajectory …