Infrastructure and Projects

Infrastructure and Projects

About Us | Infrastructure and Projects | Partnerships and Industry Involvement | Frequently Asked Questions | Contact Us

FDOT is investing in various emerging technology projects within the CoG area on several corridors in partnership with CoG and UF as shown on the I-STREET corridors map. These corridors and proposed emerging technologies can be made available to I-STREET Partners to test their proposed I-STREET Solutions. All these corridors (including I-75) are connected to the CoG’s Smartraffic Center using the City’s communications network. CoG has several ITS deployments such as traffic cameras, travel time data collection devices, and arterial dynamic message signs on a few corridors. CoG also manages and operates signals for the Gainesville and surrounding areas including the City of Alachua. The traffic signal controllers are Naztec 980 version and run on central system software at CoG’s Smartraffic facility.

UF Test Bed Corridors

I-STREET Partners may opt to use these corridors to test their Solutions or may request other corridors within CoG City Limits.  Developers may identify opportunities to improve existing and proposed systems in this region to support demonstration or testing of their proposed I-STREET Solution(s). Such recommendations should be submitted to the I-STREET Team along with the RFI response or identified after the proposed solution is selected for further discussion, potentially leading to demonstration or testing.

Detailed information regarding the specific equipment available at a particular location or corridor may be obtained from the City of Gainesville (see contacts at the end of the RFI).

Summary details for projects:

Project Name Description Contact Email
I-75 Florida’s Regional Advanced Mobility Elements (FRAME) This project will optimize the use of transportation infrastructure for improved safety and mobility. Through the project road condition information will be disseminated through the Florida 511 smartphone app and website.  Advanced transportation management technologies will be deployed such as Adaptive Signal Control Technology (ASCT); Multimodal Intelligent Traffic Signal System (MMITSS) with Intelligent Signal (I-SIG) to emit Signal Phasing and Timing (SPaT) data, Pedestrian Signal (PED-SIG) safety technology, Transit Signal Priority (TSP), Freight Signal Priority (FSP) and Emergency Vehicle Preemption (PREEMPT) on select corridors. New arterial technologies are used to improve operations, monitor traffic and infrastructure and add data-driven signal performance measures on select corridors. Connected vehicle OBU’s will be used for transit buses to increase travel time reliability and on-time performance. Advanced safety systems will be deployed through V2I and mobile app technology. Transportation system performance data will be collected, analyzed and disseminated. Fred Heery
UF Accelerated Innovation Deployment (AID) Demonstration project This project plans to deploy and test pedestrian and bicycle safety applications (active or passive) at 13 signalized intersections and seven (7) mid-block crossings using CV technologies within the core of the UF campus. The goal of the project is to reduce pedestrian and bicycle crashes and conflicts. The routes are SR 26 (University Avenue), US 441 (SW 13th Street), Museum Road and Gale Lemerand Drive. Approximately, 20 RSUs and passive pedestrian detection are anticipated to be deployed. Fred Heery
Gainesville SPaT Trapezium This project will deploy and test connected vehicle technologies and applications along four roads forming a trapezium surrounding the University of Florida main campus. The goal of the project is to improve travel time reliability, safety, throughput, and traveler information. This project will also deploy pedestrian and bicyclist safety applications for both web-based and/or Smartphone-based applications. Raj Ponnaluri
Traffic Signal Control with Connected and Autonomous Vehicles in the Traffic Stream: The project is at the intersection of several different disciplines (optimization, sensors, automated vehicles, transportation engineering) required to produce a real-time engineered system that depends on the seamless integration of several components: sensor functionality, connected and autonomous vehicle information communication, signal control optimization strategy, missing and erroneous information, etc. The project develops and implements optimization processes and strategies considering a seamless fusion of multiple data sources, as well as a mixed vehicle stream (autonomous, connected, and conventional vehicles) under real-world conditions of uncertain and missing data. Dr. Lily Elefteriadou
Development and Testing of Optimized Autonomous and Connected Vehicle Trajectories at Signalized Intersections The main objective of this project is to refine an existing optimization algorithm and develop and test the necessary software and hardware for enhancing traffic signal control operations simultaneously with vehicle trajectories, when the traffic stream consists of connected vehicles, autonomous vehicles, as well as conventional vehicles (i.e., with no operating connectivity or automation.) The algorithm is capable of optimizing simultaneously vehicle trajectories of automated vehicles together with the signal control patterns at the intersection. Dr. Lily Elefteriadou
Testbed Initiative Transit Components Develop sensor technology that can detect bicycle usage per rack position. This will increase use of ITS technology in transit, improve transit and bicycle mode attractiveness, and maximize cost effectiveness of infrastructure investments by better understanding travel patterns of bicycle users. Dr. Yong-Kyu Yoon
Data Management and Analytics UF in collaboration with FDOT and CoG is planning to develop a data analytics platform for assembling and analyzing the wealth of data expected from the new instrumentation, as well as for existing data currently obtained but not analyzed or synthesized. The objective is to design and maintain a data warehouse to process and archive data generated by the UF smart testbed. Dr. Sanjay Ranka