WTGCN: wavelet transform graph convolution network for pedestrian trajectory prediction
W Chen, H Sang, J Wang, Z Zhao - International Journal of Machine …, 2024 - Springer
The task of pedestrian trajectory prediction remains challenging due to variable scenarios,
complex social interactions, and uncertainty in pedestrian motion. Previous trajectory …
complex social interactions, and uncertainty in pedestrian motion. Previous trajectory …
Non-probability sampling network based on anomaly pedestrian trajectory discrimination for pedestrian trajectory prediction
Q Liu, H Sang, J Wang, W Chen, Y Liu - Image and Vision Computing, 2024 - Elsevier
Pedestrian trajectory prediction in first-person view is an important support for achieving fully
automated driving in cities. However, existing pedestrian trajectory prediction methods still …
automated driving in cities. However, existing pedestrian trajectory prediction methods still …
Multimodal vehicle trajectory prediction and integrated threat assessment algorithm based on adaptive driving intention
X Zhang, J Cai, F Chen, R Cheng - Chaos, Solitons & Fractals, 2024 - Elsevier
As autonomous driving and connected communication technologies advance swiftly, vehicle
trajectory prediction has become increasingly significant. The motion of a vehicle is …
trajectory prediction has become increasingly significant. The motion of a vehicle is …
DSTCNN: Deformable spatial-temporal convolutional neural network for pedestrian trajectory prediction
W Chen, H Sang, J Wang, Z Zhao - Information Sciences, 2024 - Elsevier
Pedestrian trajectory prediction holds significant research value in service robots,
autonomous driving, and intelligent monitoring. Currently, most pedestrian trajectory …
autonomous driving, and intelligent monitoring. Currently, most pedestrian trajectory …
Navigation of autonomous mobile robots in dynamic unknown environments based on dueling double deep q networks
K Ozdemir, A Tuncer - Engineering Applications of Artificial Intelligence, 2025 - Elsevier
This study focuses on applying the algorithm of Dueling Double Deep Q Networks to create
a robust and adaptable navigation system for autonomous robots. The main objective of the …
a robust and adaptable navigation system for autonomous robots. The main objective of the …
IGGCN: Individual-guided graph convolution network for pedestrian trajectory prediction
W Chen, H Sang, J Wang, Z Zhao - Digital Signal Processing, 2025 - Elsevier
Accurately predicting the future trajectory of pedestrians is crucial for applications such as
autonomous driving and robot navigation. Graph convolution is widely used in trajectory …
autonomous driving and robot navigation. Graph convolution is widely used in trajectory …
A new hybrid information fusion method for trajectory prediction
T Yang, G Wang, J Lai, Y Wang - Multimedia Tools and Applications, 2024 - Springer
Pedestrian trajectory prediction has numerous applications in various fields, such as
autonomous driving, advanced video surveillance, etc. The performance of trajectory …
autonomous driving, advanced video surveillance, etc. The performance of trajectory …