A deep learning approach for port congestion estimation and prediction
This study proposes high-frequency container port congestion measures based on
Automatic Identification System (AIS) data. Vessel movement information of 3,957 container …
Automatic Identification System (AIS) data. Vessel movement information of 3,957 container …
Bio-lstm: A biomechanically inspired recurrent neural network for 3-d pedestrian pose and gait prediction
X Du, R Vasudevan… - IEEE Robotics and …, 2019 - ieeexplore.ieee.org
In applications, such as autonomous driving, it is important to understand, infer, and
anticipate the intention and future behavior of pedestrians. This ability allows vehicles to …
anticipate the intention and future behavior of pedestrians. This ability allows vehicles to …
Time series analysis and modeling to forecast: A survey
F Dama, C Sinoquet - arXiv preprint arXiv:2104.00164, 2021 - arxiv.org
Time series modeling for predictive purpose has been an active research area of machine
learning for many years. However, no sufficiently comprehensive and meanwhile …
learning for many years. However, no sufficiently comprehensive and meanwhile …
DACR-AMTP: adaptive multi-modal vehicle trajectory prediction for dynamic drivable areas based on collision risk
P Cong, Y Xiao, X Wan, M Deng, J Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate vehicle trajectory prediction in autonomous driving technology poses significant
challenges due to the varying driving states of different vehicles, their motion patterns, and …
challenges due to the varying driving states of different vehicles, their motion patterns, and …
Artificial intelligence for vehicle behavior anticipation: Hybrid approach based on maneuver classification and trajectory prediction
Innovative technologies and naturalistic driving data sources provide a great potential to
develop reliable autonomous driving systems. Understanding the behaviors of surrounding …
develop reliable autonomous driving systems. Understanding the behaviors of surrounding …
Long-term occupancy grid prediction using recurrent neural networks
M Schreiber, S Hoermann… - … Conference on Robotics …, 2019 - ieeexplore.ieee.org
We tackle the long-term prediction of scene evolution in a complex downtown scenario for
automated driving based on Lidar grid fusion and recurrent neural networks (RNNs). A bird's …
automated driving based on Lidar grid fusion and recurrent neural networks (RNNs). A bird's …
[PDF][PDF] Forecasting COVID-19 Infection Using Encoder-Decoder LSTM and Attention LSTM Algorithms.
K Alakkari, AA Subhi, H Alkattan, A Kadi… - Journal of Intelligent …, 2023 - researchgate.net
The COVID-19 epidemic has in fact placed the whole community in a dire predicament that
has led to numerous tragedies, including an economic downturn, political unrest, and job …
has led to numerous tragedies, including an economic downturn, political unrest, and job …
Exploiting wavelet recurrent neural networks for satellite telemetry data modeling, prediction and control
C Napoli, G De Magistris, C Ciancarelli… - Expert Systems with …, 2022 - Elsevier
Multidimensional times series prediction is a challenging task. Only recently the increased
data availability has made it possible to tackle with such problems. In this work we devised a …
data availability has made it possible to tackle with such problems. In this work we devised a …
Transferable and adaptable driving behavior prediction
While autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient, transferable, and …
driving, humans have long mastered the essence of driving with efficient, transferable, and …
Maneuver-based trajectory prediction for self-driving cars using spatio-temporal convolutional networks
B Mersch, T Höllen, K Zhao… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
The ability to predict the future movements of other vehicles is a subconscious and effortless
skill for humans and key to safe autonomous driving. Therefore, trajectory prediction for …
skill for humans and key to safe autonomous driving. Therefore, trajectory prediction for …