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 …
A survey on trajectory-prediction methods for autonomous driving
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
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 …
Self-driving cars: A survey
We survey research on self-driving cars published in the literature focusing on autonomous
cars developed since the DARPA challenges, which are equipped with an autonomy system …
cars developed since the DARPA challenges, which are equipped with an autonomy system …
A review of motion planning for highway autonomous driving
L Claussmann, M Revilloud, D Gruyer… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …
that they will sell their driving automation modes in the 2020s. This technology raises …
Multimodal trajectory predictions for autonomous driving using deep convolutional networks
Autonomous driving presents one of the largest problems that the robotics and artificial
intelligence communities are facing at the moment, both in terms of difficulty and potential …
intelligence communities are facing at the moment, both in terms of difficulty and potential …
Autonomous vehicle perception: The technology of today and tomorrow
J Van Brummelen, M O'brien, D Gruyer… - … research part C …, 2018 - Elsevier
Perception system design is a vital step in the development of an autonomous vehicle (AV).
With the vast selection of available off-the-shelf schemes and seemingly endless options of …
With the vast selection of available off-the-shelf schemes and seemingly endless options of …
Robust multimodal vehicle detection in foggy weather using complementary lidar and radar signals
Vehicle detection with visual sensors like lidar and camera is one of the critical functions
enabling autonomous driving. While they generate fine-grained point clouds or high …
enabling autonomous driving. While they generate fine-grained point clouds or high …