Multiclass Information Flow Propagation Control under Vehicle-to-Vehicle Communication Environments
Jian Wang, Srinivas Peeta, Lili Lu, Tao Li

TL;DR
This paper introduces a queuing-based control model for managing multi-class information flow in vehicle-to-vehicle communication environments, enabling targeted and timely information dissemination for traffic management.
Contribution
It develops a novel two-layer model combining integro-differential equations and traffic flow dynamics to control and analyze multi-class information propagation in V2V systems.
Findings
Analytical solutions for informed vehicle density under homogeneous traffic.
Impact of communication service rate on information spread and coverage.
Numerical methods for estimating control parameter effects on propagation speed.
Abstract
Most existing models for information flow propagation in a vehicle-to-vehicle (V2V) communications environment are descriptive. They lack capabilities to control information flow, which may preclude their ability to meet application needs, including the need to propagate different information types simultaneously to different target locations within corresponding time delay bounds. This study proposes a queuing-based modeling approach to control the propagation of information flow of multiple classes. Two control parameters associated with a vehicle are leveraged to control the propagation performance of different information classes. A two-layer model is developed to characterize the information flow propagation wave (IFPW) under the designed queuing strategy. The upper layer is formulated as integro-differential equations to characterize the spatiotemporal information dissemination…
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