Development of a Connected Corridor Real-Time Data-Driven Traffic Digital Twin Simulation Model

Smart cities—being equipped with connected infrastructure—receive significant real-time traffic data. In this paper, a data-driven connected corridor traffic simulation model, i.e., a digital twin, is developed that leverages real-time data streams to model the current traffic state and provide dynamic feedback on traffic and environmental performance measures, e.g., travel time, speed, energy consumption, and vehicular emissions. The developed digital twin model architecture uses real-time 6-min volume aggregate data and 0.1 Hz to 10 Hz signal indication data as input to simulate the connected corridor using a traffic modeling software microscopic simulation. Dynamic data retrieval and transfer from the simulation model are enabled using the software’s COM feature and a Flask web server. The robustness and feasibility of the digital twin architecture and the generated performance measure reasonableness are demonstrated on a smart corridor test bed. Such a model can be used to monitor and provide insights on the impacts of intelligent transportation system technologies on connected corridor traffic and environmental performance.