Leveraging digital twin and game-engine for traffic simulations and visualizations - Rundel, Samuel; De Amicis, Raffaele (Frontiers in Virtual Reality, 2023)
Combined with simulation software packages, City Information Models allow analysts and decision-makers to explore 'what-if?' questions and scenarios for various engineering and strategic applications. In this context, crowd and traffic simulations are most commonly utilized. Urban intelligent traffic management and pedestrian flow analysis greatly benefits from the latest generation of 3D City Information Models created from accurate urban-scale geospatial information. Analysis and simulation tools based on geometric, semantic, morphological, and structural information at the urban scale level offer the scientific foundation for all the activities required for identifying, detecting, planning, training, and analyzing vulnerability that may threaten human lives in urban environments. Nevertheless, the literature research showed that samples of operational Digital Twins incorporating simulation capabilities are impracticable for small municipalities and rural, low-income communities due to their complex infrastructure, hardware, and data requirements. It is desirable to reduce the requirements for these Digital Twins and still be capable of running comprehensive and accurate simulations based on urban-scale geospatial information. This article proposes an innovative framework and workflow capable of generating an operational Digital Twin and its visualization in the form of a 3D model using a procedural approach. The Digital Twin is connected with the traffic simulation SUMO and the Game Engine Unity for visualization using the TraCI middleware. The middleware is extended with additional functionalities and acts as an authoring tool. Unity allows visualizations in VR. The entire framework can be run on a single, standalone computer and is ready in a matter of minutes. The proposed framework for integrating modeling, simulation, and visualization of operational Digital Twins can help guide better decision-making for both rural areas as well as cities.