IntelliDrive is an initiative developed by United States Department of Transportation (USDOT) that aims to enable safe, interoperable networked wireless communications among vehicles, the infrastructure, and passengers' personal communications devices. IntelliDrive technology has the ability to provide data that would be helpful in enhancement of the existing traffic management applications. IntelliDrive data has attributes that cannot be measured using traditional surveillance technology and which can be used for the development of new traffic management and traveler information applications. The traffic responsive plan selection (TRPS) mode of operation is used in coordinated traffic network to improve the performance of the system. This mode of operation has the ability to implement the best possible timing plan for the existing traffic conditions by switching between timing plans. The data from IntelliDrive technology can be utilized in the traffic responsive mode to improve the system performance by reducing the overall delay in the system. This paper proposes a system that can be used to integrate the data obtained from the IntelliDrive technology to the traffic responsive mode of operation. The proposed method utilizes the number of stops and delay of the vehicles in an intersection as a basis for the implementation of the best timing plan for the prevailing traffic condition. The study shows that using the IntelliDrive based TRPS results in the selection of the traffic plan that minimizes the delay of the system and thus results in better system performance compared to the traditional traffic responsive mechanism. / Master of Science

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.

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