Lake water temperature modeling in an era of climate change: Data sources, models, and future prospects
Lake thermal dynamics have been considerably impacted by climate change, with potential
adverse effects on aquatic ecosystems. To better understand the potential impacts of future …
adverse effects on aquatic ecosystems. To better understand the potential impacts of future …
Mapping the knowledge domain of soft computing applications for emergency evacuation studies: A scientometric analysis and critical review
Emergency evacuation is viewed as a common strategy adopted during the disaster
preparedness stage of evacuation to ensure the safety of potentially affected populations. In …
preparedness stage of evacuation to ensure the safety of potentially affected populations. In …
Pedestrian behavior prediction using deep learning methods for urban scenarios: A review
The prediction of pedestrian behavior is essential for automated driving in urban traffic and
has attracted increasing attention in the vehicle industry. This task is challenging because …
has attracted increasing attention in the vehicle industry. This task is challenging because …
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 …
Advancing crowd forecasting with graphs across microscopic trajectory to macroscopic dynamics
The high-density multi-directional passenger crowd within large transportation hubs raises
practical concerns related to degraded flow conditions and possible safety hazards, but also …
practical concerns related to degraded flow conditions and possible safety hazards, but also …
Predicting pedestrian trajectories at different densities: A multi-criteria empirical analysis
Predicting human trajectories is a challenging task due to the complexity of pedestrian
behavior, which is influenced by external factors such as the scene's topology and …
behavior, which is influenced by external factors such as the scene's topology and …
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 …
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 …
Incorporating driving knowledge in deep learning based vehicle trajectory prediction: A survey
Z Ding, H Zhao - IEEE Transactions on Intelligent Vehicles, 2023 - ieeexplore.ieee.org
Vehicle Trajectory Prediction (VTP) is one of the key issues in the field of autonomous
driving. In recent years, more researchers have tried applying Deep Learning methods and …
driving. In recent years, more researchers have tried applying Deep Learning methods and …