Over the last decade, extensive research efforts have been placed on performance evaluation and the benefits of innovative CV applications. Findings indicate that CV technology can effectively mitigate the safety, mobility, and environmental challenges experienced on transportation networks. Most of research evaluated CV technology through simulation studies. However, a field study provides a more ideal method of assessing CV technology effectiveness. Therefore, a field study to obtain the actual effectiveness of CV technology was warranted, to validate previous findings, and to add to the body of knowledge surrounding this topic. This thesis presents both a field study and simulation evaluation of the effectiveness of CV smartphone technology on a 1.1 mile segment of State Road 121, containing five intersections, in Gainesville, Florida. Field observations were conducted using a CV application, developed by Connected Signals, Inc., that uses a smartphone application, called EnLighten, to communicate intersection information to driver’s smartphone, which serves as a vehicle on-board unit.
Traffic operation and safety performance was evaluated using start-up lost time, discharge distribution model, and speed harmonization. Findings show that the CV smartphone technology improved intersection performance with a reduction in start-up lost time of approximately 86%. Additionally, driving safety improved with a reduction in speed variability by nearly 61% between vehicles in a specific lane for a 100% CV penetration rate. Cost analyses of deploying CV smartphone technology indicate that implementation may result in an average total economic cost savings associated with crashes of nearly $6.8 million at the study site, and approximately $5.6 billion statewide.
Findings of the simulation evaluation revealed that the CV technology improved performance of intersections operating at a Level of Service (LOS) B or better, compared to lower operating levels. Operational performance improved at intersections operating at a LOS C with a 30% to 60% CV penetration rate.
| Identifer | oai:union.ndltd.org:unf.edu/oai:digitalcommons.unf.edu:etd-1927 |
| Date | 01 January 2019 |
| Creators | Mjogolo, Festo |
| Publisher | UNF Digital Commons |
| Source Sets | University of North Florida |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | UNF Graduate Theses and Dissertations |
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