LiRTest: augmenting LiDAR point clouds for automated testing of autonomous driving systems
With the tremendous advancement of Deep Neural Networks (DNNs), autonomous driving
systems (ADS) have achieved significant development and been applied to assist in many …
systems (ADS) have achieved significant development and been applied to assist in many …
An efficient caching policy for content retrieval in autonomous connected vehicles
Connected vehicles will enable the smart and autonomous transportation systems in the
future. Cellular Vehicle-to-Everything (C-V2X) communication will provide wireless …
future. Cellular Vehicle-to-Everything (C-V2X) communication will provide wireless …
Age of processing-based data offloading for autonomous vehicles in multirats open ran
A Ndikumana, KK Nguyen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Today, vehicles use smart sensors to collect data from the road environment. This data is
often processed onboard of the vehicles, using expensive hardware. Such onboard …
often processed onboard of the vehicles, using expensive hardware. Such onboard …
[HTML][HTML] Where to from here? On the future development of autonomous vehicles from a cognitive systems perspective
Self-driving cars not only solve the problem of navigating safely from location A to location B;
they also have to deal with an abundance of (sometimes unpredictable) factors, such as …
they also have to deal with an abundance of (sometimes unpredictable) factors, such as …
[HTML][HTML] Intelligent task offloading in fog computing based vehicular networks
Connected vehicles in vehicular networks will lead to a smart and autonomous
transportation system. These vehicles have a large number of applications that require …
transportation system. These vehicles have a large number of applications that require …
Cyber-physical system with IoT-based smart vehicles
AA Alshdadi - Soft Computing, 2021 - Springer
Nowadays, smart vehicles can exchange data through various communication protocols in
response to technological developments in smart transport systems. Smart vehicles show …
response to technological developments in smart transport systems. Smart vehicles show …
[HTML][HTML] Optical diffractive convolutional neural networks implemented in an all-optical way
Y Yu, Y Cao, G Wang, Y Pang, L Lang - Sensors, 2023 - mdpi.com
Optical neural networks can effectively address hardware constraints and parallel computing
efficiency issues inherent in electronic neural networks. However, the inability to implement …
efficiency issues inherent in electronic neural networks. However, the inability to implement …
A novel deep reinforcement learning-based approach for task-offloading in vehicular networks
Next-generation vehicular networks will impose unprecedented computation demand due to
the wide adoption of compute-intensive services with stringent latency requirements …
the wide adoption of compute-intensive services with stringent latency requirements …
Corrfl: correlation-based neural network architecture for unavailability concerns in a heterogeneous iot environment
The Federated Learning (FL) paradigm faces several challenges that limit its application in
real-world environments. These challenges include the local models' architecture …
real-world environments. These challenges include the local models' architecture …
Real-time dynamic map with crowdsourcing vehicles in edge computing
Autonomous driving perceives surroundings with line-of-sight sensors that are compromised
under environmental uncertainties. To achieve real time global information in high definition …
under environmental uncertainties. To achieve real time global information in high definition …