Modeling Information Propagation Along Traffic on Two Parallel Roads
IntelliDrive systems, including inter-vehicle communication and vehicle infrastructure integration, aim to improve safety, mobility, and efficiency of transportation. They build on the wireless ad hoc network technologies, enabling vehicles to communicate with roadside infrastructure and with each other. The process of information propagation in a multi-hop network underlies the system design and efficiency. As of now, the research has been restricted to a single road of traffic. This work expands the study of information propagation to two parallel roads, a step further towards the discrete network case. This thesis presents two methodologies to model the process of information propagation. By identifying an approximate Bernoulli process, we are able to derive the expectation and variance of propagation distance. A road separation distance of square root of 3 over 2 times the transmission range distinguishes two cases for approximating the success probability in the Bernoulli process. In addition, our results take the single road as a special case. The numerical test shows that the developed approximation works well. This work further identities a Markov property for instantaneous information propagation along two parallel roads based on two types of transmission regions. Communication capable vehicles are assumed to follow two homogeneous Poisson processes on both roads. The Markov property enables us to derive exact expectation and variance of the propagation distance and further, obtain a recursive formula for the probability distribution of successful propagation distance. The developed formulas enable numerical calculation of the characteristics of propagation process. We hope this research will shed light on studies of vehicular ad hoc networks on more general discrete roadway networks.
Yin, Kai (2010). Modeling Information Propagation Along Traffic on Two Parallel Roads. Master's thesis, Texas A&M University. Available electronically from