Toward performing image classification and object detection with convolutional neural networks in autonomous driving systems: A survey
T Turay, T Vladimirova - IEEE Access, 2022 - ieeexplore.ieee.org
Nowadays Convolutional Neural Networks (CNNs) are being employed in a wide range of
industrial technologies for a variety of sectors, such as medical, automotive, aviation …
industrial technologies for a variety of sectors, such as medical, automotive, aviation …
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 …
Vulnerable road users and connected autonomous vehicles interaction: A survey
A Reyes-Muñoz, J Guerrero-Ibáñez - Sensors, 2022 - mdpi.com
There is a group of users within the vehicular traffic ecosystem known as Vulnerable Road
Users (VRUs). VRUs include pedestrians, cyclists, motorcyclists, among others. On the other …
Users (VRUs). VRUs include pedestrians, cyclists, motorcyclists, among others. On the other …
Learning to predict vehicle trajectories with model-based planning
Predicting the future trajectories of on-road vehicles is critical for autonomous driving. In this
paper, we introduce a novel prediction framework called PRIME, which stands for Prediction …
paper, we introduce a novel prediction framework called PRIME, which stands for Prediction …
Trajectory prediction for heterogeneous traffic-agents using knowledge correction data-driven model
There is a dilemma regarding the accuracy and reality of vehicle trajectory prediction.
Balancing and predicting the effective trajectory is a topic of debate in autonomous driving …
Balancing and predicting the effective trajectory is a topic of debate in autonomous driving …
State estimation and motion prediction of vehicles and vulnerable road users for cooperative autonomous driving: A survey
The recent progress in autonomous vehicle research and development has led to
increasingly widespread testing of fully autonomous vehicles on public roads, where …
increasingly widespread testing of fully autonomous vehicles on public roads, where …
A survey on map-based localization techniques for autonomous vehicles
A Chalvatzaras, I Pratikakis… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Autonomous vehicles integrate complex software stacks for realizing the necessary iterative
perception, planning, and action operations. One of the foundational layers of such stacks is …
perception, planning, and action operations. One of the foundational layers of such stacks is …
Vehicle trajectory prediction works, but not everywhere
Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the
industry and research communities have acknowledged the need for such a pillar by …
industry and research communities have acknowledged the need for such a pillar by …
Multi-view fusion of sensor data for improved perception and prediction in autonomous driving
We present an end-to-end method for object detection and trajectory prediction utilizing multi-
view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye …
view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye …
Vetaverse: A survey on the intersection of Metaverse, vehicles, and transportation systems
Since 2021, the term" Metaverse" has been the most popular one, garnering a lot of interest.
Because of its contained environment and built-in computing and networking capabilities, a …
Because of its contained environment and built-in computing and networking capabilities, a …