Development and Testing of Optimized Autonomous and Connected Vehicle Trajectories at Signalized Intersections

016559512017Final Report (August 2015 - November 2017)PDFTech ReportFDOT Contract BDV31-977-45AlgorithmsIntelligent vehiclesMobile communication systemsOptimizationSignalized intersectionsTestingTraffic signal control systemsVehicle designVehicle trajectoriesAutomated vehiclesconnected vehiclessignal controloptimizationUnited StatesFloridaUniversity of Florida. Transportation InstituteFlorida. Dept. of TransportationElefteriadou, LilyPourmehrab, MahmoudEmami, PatrickOmidvar, AschkanLetter, ClarkNeal, PatrickKiriazis, RebeccaRanka, SanjayCrane, CarlRidgeway, ShannonUniversity of Florida. Transportation InstituteFlorida. Dept. of TransportationNTL-INTELLIGENT TRANSPORTATION SYSTEMS-INTELLIGENT TRANSPORTATION SYSTEMSNTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Control DevicesUS Transportation CollectionSignificant improvements in automated and connected vehicle technologies are expected to create a revolution in how we move and move things. Automated vehicles can operate using a variety of sensors such as GPS, lidar, radar, and smart cameras, as well as terrain information, and they have the ability to communicate with infrastructure as well as surrounding vehicles. The objectives of this research were to develop, test, and deploy an intelligent real-time intersection traffic control system in order to optimize simultaneously signal control and automated vehicle trajectories when the traffic stream consists of autonomous, connected, and conventional vehicles. The system developed was first simulated in MATLAB. Simulation showed that the proposed system can minimize the total travel time at an isolated intersection. The system developed was also tested at the Florida Department of Transportation\u2019s Traffic Engineering Research Laboratory (FDOT TERL) facility. This report provides an overview of the hardware and software developed for the project, including a local server, DSRC (dedicated short range communications) receiver for the server, interface to the signal controller, sensor fusion system, radio communication software and hardware for vehicle to infrastructure communications. The system was tested under different scenarios. The outputs and video footage (http://avian.essie.ufl.edu/gallery/) showed that the system is capable of providing optimal trajectories to automated vehicles in order to reduce delays. Future work should expand the algorithm to consider congested conditions, lane changing within the communications range, and the presence of pedestrians and bicycles