This project evaluates using traffic simulation, the performance of a mixed traffic composition of Connected and Autonomous Vehicles (CAV) and conventional or human-driven vehicles, in comparison with the performance of the existing traffic composition of only conventional vehicles on a freeway segment. The introduction of CAVs into the existing transportation system is a phase in the evolution of automobile traffic currently generating a lot of concerns and questions that needs to be answered before the full deployment of these vehicles. Traffic simulation presents a safer and cost-effective approach to evaluating this innovative technology when compared with real world testing. Connected and autonomous vehicles (CAV) are designed to improve traffic operations, as the difference in their driving behavior from regular vehicles suggests a reasonable tendency to change the traffic flow pattern. However the issue being examined in this project is whether there would be a significant change in traffic operations resulting from their deployment, and also to verify whether the change is an improvement of the existing traffic condition in terms of performance measures used for the evaluation. Data was collected from the I-95 Freeway in South Florida, and used in the development of a traffic microsimulation model, in VISSIM. The model was calibrated using minimum error algorithm implemented in MATLAB to determine the optimal value of the two model parameters considered -- stand still distance (CC0), and headway time (CC1). The calibrated model was used as the base model and CAVs are incorporated into the base model in 10% increment, to examine their effect on the base model. The performance measures are average hourly speed, hourly traffic volume, travel time, delay, and safety. Findings show that for every increment in CAV market penetration, there is a change of 6.52% - 48% in the capacity of the freeway, 40% reduction in travel time, more than 30% reduction in delay per vehicle, more than 26% increase in average speed of the traffic at high demand volumes. / A Thesis submitted to the Department of Civil and Environmental Engineering in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester 2018. / July 9, 2018. / Connected technology, Freeway, VISSIM / Includes bibliographical references. / John O. Sobanjo, Professor Directing Thesis; Eren Erman Ozguven, Committee Member; Maxim Dulebenets, Committee Member.
Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_647310 |
Contributors | Theophilus, Oluwatosin Paul (author), Sobanjo, John Olusegun, 1958- (professor directing thesis), Ozguven, Eren Erman (committee member), Dulebenets, Maxim A. (committee member), Florida State University (degree granting institution), College of Engineering (degree granting college), Department of Civil and Environmental Engineering (degree granting departmentdgg) |
Publisher | Florida State University |
Source Sets | Florida State University |
Language | English, English |
Detected Language | English |
Type | Text, text, master thesis |
Format | 1 online resource (127 pages), computer, application/pdf |
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