A Fluid Mechanics-Based Model to Estimate VINET Capacity in an Urban Scene

Jiujun Cheng, Guiyuan Yuan, Meng Chu Zhou, Shangce Gao, Cong Liu, Changjun Jiang

Research output: Contribution to journalArticlepeer-review

Abstract

Accurate estimation of network capacity is very important for Vehicular Infrastructure-based NETwork (VINET) in an urban scene that may involve greatly dynamic typology and complex driving conditions. The node mobility, network behavior, and network scale of a VINET are different from those of a wireless network, and, therefore, the existing capacity estimation methods of wireless networks cannot be used to estimate VINET capacity. In addition, most existing studies on VINET capacity only derive asymptotic descriptions when the number of nodes is large enough. In this work, a novel approach is proposed for the modeling and calculating VINET capacity. More specifically, we first analyze communication characteristics in a VINET, and introduce two transmission modes, i.e., a vehicle-based mode and a Road Side Unit (RSU)-based one. Then, we propose a probability-based transmission mode selecting strategy with which vehicle nodes can choose either transmission mode independently and such choice is probabilistic. Next, we analyze the characteristics of an RSU-based mode, divide a VINET into a number of communities according to the position and communication range of RSUs, and derive the capacity contributed by an RSU-based mode. Then, we calculate the capacity contributed by a vehicle-based mode based on fluid mechanics. Finally, the VINET capacity can be calculated. The proposed VINET capacity estimation approach is validated to be consistent with simulation results.

Original languageEnglish (US)
JournalIEEE Transactions on Intelligent Transportation Systems
DOIs
StateAccepted/In press - 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Keywords

  • VINET capacity
  • Vehicular infrastructure-based networks
  • fluid mechanics.
  • interference community

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