United States Department of Transportation
i
Extended Development and Testing of Optimized Signal Control With Autonomous and Connected Vehicles
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2021-09-14
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[PDF-15.09 MB]
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Edition:Final Report
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Abstract:Previous work by the University of Florida and FDOT focused on the development of algorithms, software, and hardware solutions to enhance traffic signal control operations simultaneously with vehicle trajectories. These tests focused on the integration of the technology in a mixed traffic stream of autonomous, connected, and conventional vehicles. A natural extension of this work is to consider pedestrian movements and the fusion of additional existing sensors to refine the algorithm performance and further prepare it for field implementation. This report discusses the development of sensor fusion and LiDAR detection for pedestrians at a signalized intersection, and a new approach to data sharing between the infrastructure and the autonomous vehicle to maximize safety based on increased information regarding the surrounding environment. It also presents the procedure developed to accommodate pedestrians within the signal control optimization environment and the field testing conducted at FDOT’s Traffic Engineering and Research Lab (TERL) to evaluate the hardware and software system. The scenarios tested in the field provided feedback on how the system developed responds to different traffic conditions, and showed that it can serve both vehicle and pedestrian demand in all cases evaluated. It was observed that the detection method affects the timing of when a vehicle is detected, and therefore DSRC can detect vehicles from a longer distance than video. Therefore, connected vehicles may be able to place a call to the controller and get the right-of-way sooner. As a next step, this algorithm could be implemented at one or more signalized intersections for further evaluation and refinement.
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