1 code implementation • 29 Apr 2024 • Yunshuang Yuan, Monika Sester
This framework not only provides an API for flexibly prototyping the data processing pipeline and defining the gradient calculation for each agent, but also provides the user interface for interactive training, testing and data visualization.
no code implementations • 6 Feb 2024 • Yiming Xu, Hao Cheng, Monika Sester
These issues lead the existing methods to a loss of predictive diversity and adherence to the scene constraints.
1 code implementation • 27 Feb 2023 • Mengmeng Liu, Hao Cheng, Lin Chen, Hellward Broszio, Jiangtao Li, Runjiang Zhao, Monika Sester, Michael Ying Yang
Trajectory prediction for autonomous driving must continuously reason the motion stochasticity of road agents and comply with scene constraints.
no code implementations • 15 Feb 2023 • Weicheng Zhang, Hao Cheng, Fatema T. Johora, Monika Sester
Predicting trajectories of pedestrians based on goal information in highly interactive scenes is a crucial step toward Intelligent Transportation Systems and Autonomous Driving.
1 code implementation • 6 Feb 2023 • Yunshuang Yuan, Hao Cheng, Michael Ying Yang, Monika Sester
Safety is critical for autonomous driving, and one aspect of improving safety is to accurately capture the uncertainties of the perception system, especially knowing the unknown.
1 code implementation • 16 Sep 2022 • Hao Cheng, Mengmeng Liu, Lin Chen, Hellward Broszio, Monika Sester, Michael Ying Yang
This paper proposes an attention-based graph model, named GATraj, which achieves a good balance of prediction accuracy and inference speed.
no code implementations • 17 Mar 2022 • Sören Schleibaum, Jörg P. Müller, Monika Sester
Second, we apply existing XAI methods to explain the first- and second-level models of the ensemble.
Explainable artificial intelligence Explainable Artificial Intelligence (XAI)
no code implementations • 14 Jan 2022 • Yu Feng, Qing Xiao, Claus Brenner, Aaron Peche, Juntao Yang, Udo Feuerhake, Monika Sester
By comparing the detected facade openings' heights with the predicted water levels from a flood simulation model, a map can be produced which assigns per-building flood risk levels.
1 code implementation • 23 Sep 2021 • Yunshuang Yuan, Hao Cheng, Monika Sester
Sharing collective perception messages (CPM) between vehicles is investigated to decrease occlusions so as to improve the perception accuracy and safety of autonomous driving.
no code implementations • 9 May 2021 • Hao Cheng, Li Feng, Hailong Liu, Takatsugu Hirayama, Hiroshi Murase, Monika Sester
Intersections where vehicles are permitted to turn and interact with vulnerable road users (VRUs) like pedestrians and cyclists are among some of the most challenging locations for automated and accurate recognition of road users' behavior.
2 code implementations • 30 Oct 2020 • Hao Cheng, Wentong Liao, Xuejiao Tang, Michael Ying Yang, Monika Sester, Bodo Rosenhahn
In our framework, first, the spatial context between agents is explored by using self-attention architectures.
no code implementations • 21 Jun 2020 • Yu Feng, Claus Brenner, Monika Sester
Since more images are shared on social media than ever before, recent research focused on the extraction of flood-related posts by analyzing images in addition to texts.
1 code implementation • 15 Jun 2020 • Hao Cheng, Wentong Liao, Michael Ying Yang, Bodo Rosenhahn, Monika Sester
Trajectory prediction is critical for applications of planning safe future movements and remains challenging even for the next few seconds in urban mixed traffic.
1 code implementation • 14 Feb 2020 • Hao Cheng, Wentong Liao, Michael Ying Yang, Monika Sester, Bodo Rosenhahn
In inference time, we combine the past context and motion information of the target agent with samplings of the latent variables to predict multiple realistic trajectories in the future.