Special Issue "Machine Learning Algorithms for Distributed Autonomous Vehicles"
Deadline for manuscript submissions: 31 December 2023 | Viewed by 927
Autonomous vehicles are growing in popularity, with many new applications emerging in different environments and architectures, e.g., cloud/edge/fog computing. The increasing attention and need for these systems are forcing us to take a deeper look into the challenges associated with them. Resource management, i.e., appropriate allocation of resources to tasks, is one of the challenges of this type of system. Additionally, since these devices are heterogeneous, i.e., they have the different processing and transferring power, memory, sensors, bandwidth, batteries, etc., some may not be able to respond in the necessary time and with the appropriate energy expenditure and have to offload part of their computation tasks to other devices. This cooperation involves a range of challenges, such as trust and reliability, which should be considered in resource management strategies. Through machine learning algorithms, it is hoped that these systems will act intelligently and autonomously to a significant extent.
We welcome innovative contributions on optimization algorithms for autonomous vehicles. Topics include but are not limited to:
- Cloud/edge/fog computing;
- Autonomous vehicles;
- Resource management;
- Task scheduling;
- Computation offloading;
- Trusted and reliable cooperation;
- Machine learning;
- Resource allocation.
Dr. Dadmehr Rahbari
Manuscript Submission Information
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- cloud/edge/fog computing
- autonomous vehicles
- resource management
- task scheduling
- computation offloading
- trusted and reliable cooperation
- machine learning
- resource allocation