A novel generation-adversarial-network-based vehicle trajectory prediction method for intelligent vehicular networks
Prediction of the future location of vehicles and other mobile targets is instrumental in
intelligent transportation system applications. In fact, networking schemes and protocols …
intelligent transportation system applications. In fact, networking schemes and protocols …
Multi-modal trajectory prediction for autonomous driving with semantic map and dynamic graph attention network
B Dong, H Liu, Y Bai, J Lin, Z Xu, X Xu… - arXiv preprint arXiv …, 2021 - arxiv.org
Predicting future trajectories of surrounding obstacles is a crucial task for autonomous
driving cars to achieve a high degree of road safety. There are several challenges in …
driving cars to achieve a high degree of road safety. There are several challenges in …
Trajectory prediction with graph-based dual-scale context fusion
Motion prediction for traffic participants is essential for a safe and robust automated driving
system, especially in cluttered urban environments. However, it is highly challenging due to …
system, especially in cluttered urban environments. However, it is highly challenging due to …
A co-evolutionary lane-changing trajectory planning method for automated vehicles based on the instantaneous risk identification
J Wu, X Chen, Y Bie, W Zhou - Accident Analysis & Prevention, 2023 - Elsevier
Lane-changing trajectory planning (LTP) is an effective concept to control automated
vehicles (AVs) in mixed traffic, which can reduce traffic conflicts and improve overall traffic …
vehicles (AVs) in mixed traffic, which can reduce traffic conflicts and improve overall traffic …
Interacting vehicle trajectory prediction with convolutional recurrent neural networks
S Mukherjee, S Wang, A Wallace - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Anticipating the future trajectories of surrounding vehicles is a crucial and challenging task
in path planning for autonomy. We propose a novel Convolutional Long Short Term Memory …
in path planning for autonomy. We propose a novel Convolutional Long Short Term Memory …
Diverse multiple trajectory prediction using a two-stage prediction network trained with lane loss
Prior studies in the field of motion predictions for autonomous driving tend to focus on finding
a trajectory that is close to the ground truth trajectory, which is highly biased toward straight …
a trajectory that is close to the ground truth trajectory, which is highly biased toward straight …
Leveraging future relationship reasoning for vehicle trajectory prediction
Understanding the interaction between multiple agents is crucial for realistic vehicle
trajectory prediction. Existing methods have attempted to infer the interaction from the …
trajectory prediction. Existing methods have attempted to infer the interaction from the …
Modeling driver risk perception on city roads using deep learning
P Ping, Y Sheng, W Qin, C Miyajima, K Takeda - IEEE Access, 2018 - ieeexplore.ieee.org
Research on how risk is perceived by drivers is vital to driving behavior research and driving
safety. As risk can be divided into subjective and objective risk, in this paper, we focus on …
safety. As risk can be divided into subjective and objective risk, in this paper, we focus on …
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 …
plan and fast decision making capability of the system to reach their destination in the …
Multi-agent driving behavior prediction across different scenarios with self-supervised domain knowledge
How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …
autonomous driving. It is significant to have the ability to predict surrounding road …