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 …
Control of connected and automated vehicles: State of the art and future challenges
Autonomous driving technology pledges safety, convenience, and energy efficiency. Its
challenges include the unknown intentions of other road users: communication between …
challenges include the unknown intentions of other road users: communication between …
Parallel driving OS: A ubiquitous operating system for autonomous driving in CPSS
With the rapid development of autonomous driving technologies, a vast array of autonomous
driving algorithms and platforms have emerged. These algorithms and platforms are usually …
driving algorithms and platforms have emerged. These algorithms and platforms are usually …
Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Abstract Reasoning about human motion is an important prerequisite to safe and socially-
aware robotic navigation. As a result, multi-agent behavior prediction has become a core …
aware robotic navigation. As a result, multi-agent behavior prediction has become a core …
Survey of deep reinforcement learning for motion planning of autonomous vehicles
S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …
recent years related to several topics as sensor technologies, V2X communications, safety …
A systematic survey of control techniques and applications in connected and automated vehicles
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
Covernet: Multimodal behavior prediction using trajectory sets
T Phan-Minh, EC Grigore, FA Boulton… - Proceedings of the …, 2020 - openaccess.thecvf.com
We present CoverNet, a new method for multimodal, probabilistic trajectory prediction for
urban driving. Previous work has employed a variety of methods, including multimodal …
urban driving. Previous work has employed a variety of methods, including multimodal …
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 …
Trafficsim: Learning to simulate realistic multi-agent behaviors
Simulation has the potential to massively scale evaluation of self-driving systems, enabling
rapid development as well as safe deployment. Bridging the gap between simulation and …
rapid development as well as safe deployment. Bridging the gap between simulation and …
Generating useful accident-prone driving scenarios via a learned traffic prior
Evaluating and improving planning for autonomous vehicles requires scalable generation of
long-tail traffic scenarios. To be useful, these scenarios must be realistic and challenging …
long-tail traffic scenarios. To be useful, these scenarios must be realistic and challenging …