[PDF][PDF] HST-LSTM: A hierarchical spatial-temporal long-short term memory network for location prediction.

D Kong, F Wu - Ijcai, 2018 - ijcai.org
The widely use of positioning technology has made mining the movements of people
feasible and plenty of trajectory data have been accumulated. How to efficiently leverage …

Multi-scale graph-transformer network for trajectory prediction of the autonomous vehicles

D Singh, R Srivastava - Intelligent Service Robotics, 2022 - Springer
The accurate trajectory prediction is a crucial task for the autonomous vehicles that help to
plan and fast decision making capability of the system to reach their destination in the …

T-CONV: A convolutional neural network for multi-scale taxi trajectory prediction

J Lv, Q Li, Q Sun, X Wang - … conference on big data and smart …, 2018 - ieeexplore.ieee.org
Precise destination prediction of taxi trajectories can benefit many intelligent location based
services such as accurate ad for passengers. Traditional prediction approaches, which treat …

Graph Neural Network with RNNs based trajectory prediction of dynamic agents for autonomous vehicle

D Singh, R Srivastava - Applied Intelligence, 2022 - Springer
Trajectory prediction is an essential ability for the intelligent transportation system to
navigate through complex traffic scenes. In recent times, trajectory prediction has become an …

A scalable framework for trajectory prediction

P Rathore, D Kumar, S Rajasegarar… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
Trajectory prediction (TP) is of great importance for a wide range of location-based
applications in intelligent transport systems, such as location-based advertising, route …

Hybrid channel access scheduling in ad hoc networks

L Bao, JJ Garcia-Luna-Aceves - 10th IEEE International …, 2002 - ieeexplore.ieee.org
We present the hybrid activation multiple access (HAMA) protocol for ad hoc networks.
Unlike previous channel access scheduling protocols that activate either nodes or links only …

Multi-scale and multi-scope convolutional neural networks for destination prediction of trajectories

J Lv, Q Sun, Q Li… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Precise destination prediction from partial trajectories have a huge potential impact on
intelligent location-based approaches. Traditional prediction approaches, which treat …

Trip destination prediction based on a deep integration network by fusing multiple features from taxi trajectories

J Tang, J Liang, T Yu, Y **ong… - IET Intelligent Transport …, 2021 - Wiley Online Library
Trip destination prediction plays an important role in exploring urban travel patterns.
Accurate prediction can improve the efficiency of traffic management and the quality of …

Taxi-Passenger's destination prediction via GPS embedding and attention-based BiLSTM model

C Liao, C Chen, C **ang, H Huang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The prediction of taxi-passenger's destination with the partial GPS trajectory left by moving
taxis is an important yet challenging research issue. The high uncertainty of human mobility …

Trajectory prediction based on long short-term memory network and Kalman filter using hurricanes as an example

W Qin, J Tang, C Lu, S Lao - Computational Geosciences, 2021 - Springer
Trajectory data can objectively reflect the moving law of moving objects. Therefore, trajectory
prediction has high application value. Hurricanes often cause incalculable losses of life and …