Performance Analysis of Resource Allocation Algorithms for Vehicle Platoons over 5G eV2X Communication
Gulabi Mandal, Anik Roy, Basabdatta Palit

TL;DR
This paper evaluates resource allocation algorithms for vehicle platoons over 5G eV2X, using comprehensive simulations to identify optimal communication topologies and resource management strategies for improved safety and efficiency.
Contribution
It introduces a detailed simulation framework for vehicle platooning over 5G eV2X and compares different information flow topologies and resource allocation algorithms.
Findings
One-Hop IFT with MaxC/I provides best QoS performance.
MaxC/I resource allocation outperforms PF and DRR in latency and reliability.
One-Hop topology is most suitable for vehicle platooning over 5G.
Abstract
Vehicle platooning is a cooperative driving technology that can be supported by 5G enhanced Vehicle-to-Everything (eV2X) communication to improve road safety, traffic efficiency, and reduce fuel consumption. eV2X communication among the platoon vehicles involves the periodic exchange of Cooperative Awareness Messages (CAMs) containing vehicle information under strict latency and reliability requirements. These requirements can be maintained by administering the assignment of resources, in terms of time slots and frequency bands, for CAM exchanges in a platoon, with the help of a resource allocation mechanism. State-of-the-art on control and communication design for vehicle platoons either consider a simplified platoon model with a detailed communication architecture or consider a simplified communication delay model with a detailed platoon control system. Departing from existing works,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVehicular Ad Hoc Networks (VANETs) · Smart Parking Systems Research · Advanced Manufacturing and Logistics Optimization
