Vehicle trajectory prediction with lane stream attention-based LSTMs and road geometry linearization

D Yu, H Lee, T Kim, SH Hwang - Sensors, 2021 - mdpi.com
It is essential for autonomous vehicles at level 3 or higher to have the ability to predict the
trajectories of surrounding vehicles to safely and effectively plan and drive along trajectories …

Vehicle trajectory prediction using LSTMs with spatial–temporal attention mechanisms

L Lin, W Li, H Bi, L Qin - IEEE Intelligent Transportation Systems …, 2021 - ieeexplore.ieee.org
Accurate vehicle trajectory prediction can benefit a variety of intelligent transportation system
applications ranging from traffic simulations to driver assistance. The need for this ability is …

A CNN-LSTM Based Model to Predict Trajectory of Human-Driven Vehicle

S Alsanwy, H Asadi, MRC Qazani… - … on Systems, Man …, 2023 - ieeexplore.ieee.org
Vehicle trajectory prediction is essential in ensuring the safe and efficient operation of
advanced driver assistance systems (ADAS) and autonomous vehicles (AVs), as it enables …

Long short-term memory-based human-driven vehicle longitudinal trajectory prediction in a connected and autonomous vehicle environment

L Lin, S Gong, S Peeta, X Wu - Transportation research …, 2021 - journals.sagepub.com
The advent of connected and autonomous vehicles (CAVs) will change driving behavior and
travel environment, and provide opportunities for safer, smoother, and smarter road …

Intention-aware long horizon trajectory prediction of surrounding vehicles using dual LSTM networks

L Xin, P Wang, CY Chan, J Chen… - 2018 21st …, 2018 - ieeexplore.ieee.org
As autonomous vehicles (AVs) need to interact with other road users, it is of importance to
comprehensively understand the dynamic traffic environment, especially the future possible …

Vehicle trajectory prediction and generation using LSTM models and GANs

L Rossi, A Ajmar, M Paolanti, R Pierdicca - Plos one, 2021 - journals.plos.org
Vehicles' trajectory prediction is a topic with growing interest in recent years, as there are
applications in several domains ranging from autonomous driving to traffic congestion …

An LSTM network for highway trajectory prediction

F Altché, A de La Fortelle - 2017 IEEE 20th international …, 2017 - ieeexplore.ieee.org
In order to drive safely and efficiently on public roads, autonomous vehicles will have to
understand the intentions of surrounding vehicles, and adapt their own behavior …

Spatial-temporal attentive LSTM for vehicle-trajectory prediction

R Jiang, H Xu, G Gong, Y Kuang, Z Liu - ISPRS International Journal of …, 2022 - mdpi.com
Vehicle-trajectory prediction is essential for intelligent traffic systems (ITS), as it can help
autonomous vehicles to plan a safe and efficient path. However, it is still a challenging task …

ST-LSTM: Spatio-temporal graph based long short-term memory network for vehicle trajectory prediction

G Chen, L Hu, Q Zhang, Z Ren, X Gao… - … Conference on Image …, 2020 - ieeexplore.ieee.org
Autonomous vehicles need the ability to predict the trajectory of surrounding vehicles, so as
to make a rational decision planning, improve driving safety and ride comfort. In this paper, a …

A Hierarchical LSTM-Based Vehicle Trajectory Prediction Method Considering Interaction Information

H Min, X Xiong, P Wang, Z Zhang - Automotive Innovation, 2024 - Springer
Trajectory prediction is an essential component in autonomous driving systems, as it can
forecast the future movements of surrounding vehicles, thereby enhancing the decision …