TRB Pubsindex
Text Size:

Title:

A Spatial Stochastic Traffic Model for Connected Vehicles in VANETs

Accession Number:

01628140

Record Type:

Component

Abstract:

Vehicular Ad hoc NETworks (VANETs) have been envisioned to enable a variety of important applications for road traffic, and will open up some unprecedented opportunities to change the way road traffic operates. Connectivity is fundamentally required for VANETs to secure reliable dissemination of information among networked vehicles for the purpose of various VANETs applications. Due to the high mobility of vehicles, the topology of a VANET rapidly changes and connectivity is not always guaranteed especially in the case of traffic sparsity and low market penetration of networked vehicles. Thus, it is essential to examine the connectivity issue before deploying VANETs. The probabilistic distributions of inter-vehicle spacing play a crucial role in the study of connectivity. It was quite often in previous studies to use some priori distributions to model inter-vehicle spacing, or examine possible distributions via some queueing models that are not very intimate to traffic reality, or reply on some assumptions that are not very practical. This paper re-examines this issue analytically and figures out with a general set of conditions that under the free flow condition the distribution of the spatial number of vehicles along a highway is Poisson, with the corresponding inter-vehicle spacing exponentially distributed.

Supplemental Notes:

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-02574

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Guo, Jingqiu
Zhang, Yong
Wang, Yibing

Pagination:

11p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References

Subject Areas:

Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-02574

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 10:58AM