Title
Stochastic Traffic And Connectivity Dynamics For Vehicular Ad-Hoc Networks In Signalized Road Systems
Abstract
In the design and planning of vehicular ad-hoc networks, road-side infrastructure nodes are commonly used to improve the overall connectivity and communication capability of the networks, however, to determine the locations to install the infrastructure nodes for optimal performance based on the ever-changing density and connectivity dynamics of moving vehicles remains to be a challenging issue. In this paper, we introduce a stochastic traffic model to capture the space and time dynamics of vehicles in signalized urban road systems to identify poorly-connected regions for infrastructure node placements. To closely approximate the practical road conditions, we propose a density-dependent velocity profile to approximate vehicle interactions and capture platoons formation and dissipation at traffic signals. Numerical results are presented to evaluate the stochastic traffic model. In general, we show that the fluid model can adequately describe the mean behavior of the traffic stream, while the stochastic model can approximate the probability distribution well even when vehicles interact with each other as their movement is controlled by traffic lights. With the understandings of the vehicular density dynamics from the proposed model, we illustrate that connectivity dynamics of vehicles can be determined and consequent system engineering and planning can be carried out.
Year
DOI
Venue
2009
10.1109/LCN.2009.5355107
2009 IEEE 34TH CONFERENCE ON LOCAL COMPUTER NETWORKS (LCN 2009)
Keywords
Field
DocType
probability distribution,stochastic processes,stochastic model,system engineering,vehicle dynamics,computational modeling,fluid dynamics,ad hoc networks,fluid model,density dependence,vehicular ad hoc network
Mobile radio,Traffic wave,Computer science,Microscopic traffic flow model,Computer network,Stochastic process,Vehicle dynamics,Probability distribution,Stochastic modelling,Wireless ad hoc network,Distributed computing
Conference
ISSN
Citations 
PageRank 
0742-1303
2
0.43
References 
Authors
2
3
Name
Order
Citations
PageRank
Ivan Wang Hei Ho114418.54
Kin K. Leung22463183.60
John Polak3466.04