Abstract

Broadcast capacity of the entire network is one of the fundamental properties of vehicular ad hoc networks (VANETs). It measures how efficiently the information can be transmitted in the network and usually it is limited by the interference between the concurrent transmissions in the physical layer of the network. This study defines the broadcast capacity of vehicular ad hoc network as the maximum successful concurrent transmissions. In other words, we measure the maximum number of packets which can be transmitted in a VANET simultaneously, which characterizes how fast a new message such as a traffic incident can be transmitted in a VANET. Integer programming (IP) models are first developed to explore the maximum number of successful receiving nodes as well as the maximum number of transmitting nodes in a VANET. The models embed an traffic flow model in the optimization problem. Since IP model cannot be efficiently solved as the network size increases, this study develops a statistical model to predict the network capacity based on the significant parameters in the transportation and communication networks. MITSIMLab is used to generate the necessary traffic flow data. Response surface method and linear regression technologies are applied to build the statistical models. Thus, this paper brings together an array of tools to solve the broadcast capacity problem in VANETs. The proposed methodology provides an efficient approach to estimate the performance of a VANET in real-time, which will impact the efficacy of travel decision making.