Connectivity Probability Analysis for Roadside Units Location on Two-Way Streets

The main objective of this paper is to locate roadside units (RSUs) on a two-way street for assuring connectivity probability of the communication network formed by communication equipped vehicles and RSUs when traffic density is low. In this paper, connectivity probability means the probability of a vehicle accessing successfully an RSU either directly or through the relay of other vehicles (i.e. in one hop or multihop). A road segment, consisting of two lanes with vehicles moving in both directions is considered. Moreover, the effect of relaying vehicles moving in the opposite direction on the connectivity probability is taken into account. An analytical model is developed to describe the relationship between the connectivity probability and the distance between two neighbor RSUs. And the penetration rate of equipped vehicles is considered in the model. Studies taking a two-way street as a typical case showed that increasing traffic density on a lane makes it possible to increase the distance between two RSUs while assuring a connection probability of 0.85 or higher. Results also showed that when traffic density on another lane is lower than 2 veh/km, transmission range is smaller than 450 meters or the distance between two RSUs is larger than four-time transmission range, increasing traffic density on the lane achieves more advantages.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AHB15 Standing Committee on Intelligent Transportation Systems.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Wu, Zhizhou
    • Liang, Yunyi
    • Tian, Yu
    • Liu, Jiahui
  • Conference:
  • Date: 2017

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 18p
  • Monograph Title: TRB 96th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01632202
  • Record Type: Publication
  • Report/Paper Numbers: 17-06338
  • Files: TRIS, TRB, ATRI
  • Created Date: Apr 6 2017 12:28PM