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The paper presents a model for multimodal traffic signal priority control. The approach is based on an analytical model and a flexible implementation algorithm that considers real-time vehicle actuation. The analytical model considers the needs of different modes in a real-time connected vehicle environment. The model provides an optimal signal schedule that minimizes the total weighted priority request delay. The flexible implementation algorithm is designed to guarantee that the optimal signal schedule is applied with minimum negative impact on regular vehicles. The model has been tested in a simulation framework on two networks: San Mateo, California, and Anthem, Arizona. The simulation experiments showed that the model, when compared with fully actuated control, was able to reduce average delay and travel times for priority vehicles without a significant negative impact on passenger cars. The field results of implementing the priority framework in the nationally affiliated connected vehicles test bed in Anthem showed the effectiveness of the model in the real world.

Basic signal operation strategies allocate green time to different traffic movements to control the flow at an intersection. Signal control applications consider different objectives, such as coordination with multiple intersections, multimodal priority, and safety. Real-time signal control applications rely mainly on infrastructure-based detection data. With the emergence of connected vehicle technology, high-resolution data from connected vehicles will become available for signal control. This paper presents a framework that uses connected vehicle data for adaptive signal control and considers dilemma zone protection, multimodal signal priority, and coordination. Initially, the market penetration rate of connected vehicles will be low, so infrastructure-based detector actuation logic is integrated into the framework to improve performance. Simulation analysis demonstrated good results when the penetration rate was medium to high and that the actuation logic was necessary when the penetration rate was low.