Summary and Reflections on Pedestrian Trajectory Prediction in the Field of Autonomous Driving

Z Fu, K Jiang, C **e, Y Xu, J Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Pedestrian trajectory prediction is a classic and challenging scientific task that involves
complex engineering science and human factors. These challenges have spurred a …

Generating synthetic training data for deep learning-based UAV trajectory prediction

S Becker, R Hug, W Hübner, M Arens… - arxiv preprint arxiv …, 2021 - arxiv.org
Deep learning-based models, such as recurrent neural networks (RNNs), have been
applied to various sequence learning tasks with great success. Following this, these models …

Stochastic Non-Autoregressive Transformer-Based Multi-Modal Pedestrian Trajectory Prediction for Intelligent Vehicles

X Chen, H Zhang, F Deng, J Liang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Pedestrian trajectory prediction, which aims at predicting the future positions of all
pedestrians in a crowd scene given their past trajectories, is the cornerstone of autonomous …

Target-point Attention Transformer: A novel trajectory predict network for end-to-end autonomous driving

J Du, Y Zhao, H Cheng - arxiv preprint arxiv:2308.01496, 2023 - arxiv.org
In the field of autonomous driving, there have been many excellent perception models for
object detection, semantic segmentation, and other tasks, but how can we effectively use the …

MissFormer:(In-) attention-based handling of missing observations for trajectory filtering and prediction

S Becker, R Hug, W Huebner, M Arens… - … Symposium on Visual …, 2021 - Springer
In applications such as object tracking, time-series data inevitably carry missing
observations. Following the success of deep learning-based models for various sequence …

Crowd Prediction and Autonomous Navigation with Partial Observations

K Li, M Shan, S Worrall, E Nebot - 2022 IEEE 25th International …, 2022 - ieeexplore.ieee.org
Operating autonomous vehicles safely and efficiently in crowded pedestrian environments is
a challenging task, especially with partial observations. This is because autonomous …

Goal-Oriented Transformer to Predict Context-Aware Trajectories in Urban Scenarios

Á Quintanar, R Izquierdo, I Parra… - Engineering …, 2023 - mdpi.com
The accurate prediction of road user behaviour is of paramount importance for the design
and implementation of effective trajectory prediction systems. Advances in this domain have …

Pedestrian trajectory prediction with high-order interactions

N **ang, B Tian, Z Wang - Journal of Electronic Imaging, 2024 - spiedigitallibrary.org
To tackle the problem of human trajectory prediction in complex scenes, we propose a
model using hypergraph convolutional neural networks for social interaction (HGCNSI). Our …

時空間の Transformer による歩行軌跡予測モデル

笹沢成豪, 藤田悟 - 第 84 回全国大会講演論文集, 2022 - ipsj.ixsq.nii.ac.jp
論文抄録 人が歩くとき, 過去の経路や速度に加え, 周囲の人や物の配置によって歩行経路を決定
する. これらのルールをモデル化するために様々な研究が行われてきたが, **年ではニューラル …

時空間の Transformer による歩行軌跡予測

笹沢成豪, 藤田悟 - 第 85 回全国大会講演論文集, 2023 - ipsj.ixsq.nii.ac.jp
論文抄録 人は歩行時に過去の経路に加えて, 周囲の人や障害物の配置によって歩行経路を決定し
ている. この 2 つの情報による経路決定をモデル化するために, 様々な研究が行われてきた …