Computing systems for autonomous driving: State of the art and challenges
The recent proliferation of computing technologies (eg, sensors, computer vision, machine
learning, and hardware acceleration) and the broad deployment of communication …
learning, and hardware acceleration) and the broad deployment of communication …
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …
Learning lane graph representations for motion forecasting
We propose a motion forecasting model that exploits a novel structured map representation
as well as actor-map interactions. Instead of encoding vectorized maps as raster images, we …
as well as actor-map interactions. Instead of encoding vectorized maps as raster images, we …
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …
order to achieve robust and accurate scene understanding, autonomous vehicles are …
Seeing through fog without seeing fog: Deep multimodal sensor fusion in unseen adverse weather
The fusion of multimodal sensor streams, such as camera, lidar, and radar measurements,
plays a critical role in object detection for autonomous vehicles, which base their decision …
plays a critical role in object detection for autonomous vehicles, which base their decision …
Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
High definition map for automated driving: Overview and analysis
R Liu, J Wang, B Zhang - The Journal of Navigation, 2020 - cambridge.org
As one of the key enabling technologies for automated driving, High Definition (HD) Maps
have become a major research focus in recent years. While increasing research effort has …
have become a major research focus in recent years. While increasing research effort has …
Uncertainty-aware short-term motion prediction of traffic actors for autonomous driving
We address one of the crucial aspects necessary for safe and efficient operations of
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
autonomous vehicles, namely predicting future state of traffic actors in the autonomous …
End-to-end contextual perception and prediction with interaction transformer
In this paper, we tackle the problem of detecting objects in 3D and forecasting their future
motion in the context of self-driving. Towards this goal, we design a novel approach that …
motion in the context of self-driving. Towards this goal, we design a novel approach that …
Localization and mapping for robots in agriculture and forestry: A survey
Research and development of autonomous mobile robotic solutions that can perform
several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots …
several active agricultural tasks (pruning, harvesting, mowing) have been growing. Robots …