Privacy-preserving generation and publication of synthetic trajectory microdata: A comprehensive survey

JW Kim, B Jang - Journal of Network and Computer Applications, 2024 - Elsevier
The generation of trajectory data has increased dramatically with the advent and
widespread use of GPS-enabled devices. This rich source of data provides invaluable …

[HTML][HTML] A critical review of RNN and LSTM variants in hydrological time series predictions

M Waqas, UW Humphries - MethodsX, 2024 - Elsevier
The rapid advancement in Artificial Intelligence (AI) and big data has developed significance
in the water sector, particularly in hydrological time-series predictions. Recurrent Neural …

A car-following model based on trajectory data for connected and automated vehicles to predict trajectory of human-driven vehicles

D Qu, S Wang, H Liu, Y Meng - Sustainability, 2022 - mdpi.com
Connected and Automated Vehicles (CAV) have been rapidly developed, which, inevitably,
renders that human-driven and autonomous vehicles share the road. Thus, trajectory …

Bubblex: An explainable deep learning framework for point-cloud classification

F Matrone, M Paolanti, A Felicetti… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Point-cloud data are nowadays one of the major data sources for describing our
environment. Recently, deep architectures have been proposed as a key step in …

GeoAI: a review of artificial intelligence approaches for the interpretation of complex geomatics data

R Pierdicca, M Paolanti - Geoscientific Instrumentation, Methods …, 2022 - gi.copernicus.org
Researchers have explored the benefits and applications of modern artificial intelligence
(AI) algorithms in different scenario. For the processing of geomatics data, AI offers …

Vehicles trajectory prediction using recurrent VAE network

MÁ De Miguel, JM Armingol, F Garcia - IEEE Access, 2022 - ieeexplore.ieee.org
This paper presents an analysis of the implementation and performance of a deep learning
model based on Recurrent layers and Variational Auto Encoder model (VAE) architecture for …

VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformer

AD Pazho, GA Noghre, V Katariya… - Proceedings of the …, 2024 - openaccess.thecvf.com
Enhancing roadway safety has become an essential computer vision focus area for
Intelligent Transportation Systems (ITS). As a part of ITS Vehicle Trajectory Prediction (VTP) …

[HTML][HTML] Preservation of villages in Central Italy: Geomatic techniques' integration and GIS strategies for the post-earthquake assessment

F Piccinini, A Gorreja, F Di Stefano, R Pierdicca… - … International Journal of …, 2022 - mdpi.com
Historical villages represent a highly vulnerable cultural heritage; their preservation can be
ensured thanks to technological innovations in the field of geomatics and information …

Vehicle lane-changing scenario generation using time-series generative adversarial networks with an adaptative parameter optimization strategy

Y Li, F Zeng, C Han, S Feng - Accident Analysis & Prevention, 2024 - Elsevier
Connected and automated vehicles (CAVs) hold promise for enhancing transportation safety
and efficiency. However, their large-scale deployment necessitates rigorous testing across …

EscIRL: Evolving Self-Contrastive IRL for Trajectory Prediction in Autonomous Driving

S Wang, Z Chen, Z Zhao, C Mao, Y Zhou… - … Annual Conference on …, 2024 - openreview.net
While deep neural networks (DNN) and inverse reinforcement learning (IRL) have both
been commonly used in autonomous driving to predict trajectories through learning from …