Infer: Intermediate representations for future prediction
In urban driving scenarios, forecasting future trajectories of surrounding vehicles is of
paramount importance. While several approaches for the problem have been proposed, the …
paramount importance. While several approaches for the problem have been proposed, the …
Map-free trajectory prediction in traffic with multi-level spatial-temporal modeling
To handle two shortcomings of existing methods,(i) nearly all models rely on the high-
definition (HD) maps, yet the map information is not always available in real traffic scenes …
definition (HD) maps, yet the map information is not always available in real traffic scenes …
Continual Learning for Motion Prediction Model via Meta-Representation Learning and Optimal Memory Buffer Retention Strategy
Embodied AI such as autonomous vehicles suffers from insufficient long-tailed data because
it must be obtained from the physical world. In fact data must be continuously obtained in a …
it must be obtained from the physical world. In fact data must be continuously obtained in a …
An automated pipeline for advanced fault tolerance in edge computing infrastructures
The very fabric of Edge Computing is intertwined with the necessity to be able to orchestrate
and manage a huge number of heterogeneous computational resources. On top of that, the …
and manage a huge number of heterogeneous computational resources. On top of that, the …
[HTML][HTML] Methodology for multi-temporal prediction of crop rotations using recurrent neural networks
In a context of growing demand for food and the scarcity of natural resources, the
development of more sustainable agriculture is imperative. This means it is necessary to …
development of more sustainable agriculture is imperative. This means it is necessary to …
Pedestrian trajectory prediction via spatial interaction transformer network
T Su, Y Meng, Y Xu - 2021 IEEE Intelligent Vehicles …, 2021 - ieeexplore.ieee.org
As a core technology of the autonomous driving system, pedestrian trajectory prediction can
significantly enhance the function of active vehicle safety and reduce road traffic injuries. In …
significantly enhance the function of active vehicle safety and reduce road traffic injuries. In …
Uncertainty estimation for cross-dataset performance in trajectory prediction
While a lot of work has been carried on developing trajectory prediction methods, and
various datasets have been proposed for benchmarking this task, little study has been done …
various datasets have been proposed for benchmarking this task, little study has been done …
A digital twin-based motion forecasting framework for preemptive risk monitoring
Risk monitoring is a critical task in numerous industrial fields, including construction
engineering. Existing approaches primarily focus on identifying the immediate incidents of …
engineering. Existing approaches primarily focus on identifying the immediate incidents of …
Deep understanding of big geospatial data for self-driving: Data, technologies, and systems
H Wang, J Feng, K Li, L Chen - Future Generation Computer Systems, 2022 - Elsevier
With the continued development of Autonomous Vehicle System (AVS), self-driving related
technologies have attracted much attention over the past decade. In this light, we survey …
technologies have attracted much attention over the past decade. In this light, we survey …
Interaction-aware personalized vehicle trajectory prediction using temporal graph neural networks
A Abdelraouf, R Gupta, K Han - 2023 IEEE 26th International …, 2023 - ieeexplore.ieee.org
Accurate prediction of vehicle trajectories is vital for advanced driver assistance systems and
autonomous vehicles. Existing methods mainly rely on generic trajectory predictions derived …
autonomous vehicles. Existing methods mainly rely on generic trajectory predictions derived …