# A Digital Twin for Intelligent Transportation Systems in Interurban Scenarios
## 2 State of the Art on Digital Twins for Intelligent Transportation Systems
### Digital Twins of Urban Scenarios  
Urban case studies focus on the development of a digital twin of a city or a specific section of it. In this field, several research works have been conducted. For instance, ref. [12] develops a digital twin for Adaptive Traffic Signal Control (ATSC). This digital twin contains the traffic signal controller, the roads, and the updated information of the vehicles and their trajectories. The digital twin processes the information and decides how to change the traffic lights, which is communicated to the traffic controller in the real world. The metric optimized by this digital twin is the Average Accumulated Waiting Time (AAWT), defined as the total waiting time that the vehicle has experienced at all its stops. The platform used for simulation is Simulation of Urban Mobility (SUMO) [13]. This work only presents a theoretical case study; no demonstration has been carried out to prove its viability.  
The work in [14] presents another urban study that focuses on non-signalized intersections. This work designs a cooperative driving system for non-signalized intersections with the objective of avoiding full stops for connected vehicles. Two main modules are proposed: a motion module in charge of map matching with Unity [15], path planning, and scheduling of the sequence of vehicles to cross the intersection using enhanced First In FirstOut (FIFO) slot reservation; and a communication module, which analyses performance and tracks communication issues. The V2X connectivity is based on Dedicated Short-Range Communications (DSRC), Cellular V2X (C-V2X), or both. In addition, augmented reality for Human-Machine-Interface (HMI) is designed to provide guidance to the drivers. Two case studies are performed, one using a map of San Francisco, and the other involving Human-In-The-Loop (HITL) simulation.  
The work in [16] proposes a digital twin methodology to perform multi-vehicle experiments, which involves the coordinated control of several vehicles and addresses the limitations of field testing in cooperative vehicle control. A cloud platform is used to collect real-world data, and time delay and mapping accuracy are evaluated. The HMI uses web services and augmented reality (HoloLens) to visualize the digital twin. To support the HMI, the game engine Unity3D 6.1 (6000.0.47f1) is used to provide a more immersive experience. To test this method, a prototype consisting of a sand table testbed is developed, along with its corresponding twin system and a driving simulator.  
The work in [17] creates an Urban Digital Twin (UDT) to closely resemble the real world. It is a proposal for the data acquisition and representation phase, but no further processing is done with the information. The main objective is to reproduce in 3D the desired time and place by adding individual pedestrians and vehicles to the UDT model. Monocular camera lens-based Closed-Circuit Television (CCTV) is used to collect the data of the individual objects, and Unity3D is used for visualization.  
Real implementations of urban digital twins are currently under development, with European initiatives such as Digital Urban European Twins (DUET) [18], which aims to build digital twins of three cities (Flanders, Pilsen, and Athens) to understand the relationship between traffic, air quality, noise, and other urban factors. Similarly, the Low-Emission Adaptive last mile logistics supporting the 'on Demand economy' through digital twins (LEAD) project [19], is developing digital twins for six cities (Madrid, The Hague, Budapest, Lyon, Oslo, and Porto), with the objective of providing smart urban logistics that are more environmentally, socially, and economically sustainable. Several Russian cities are using the RITM3 platform to develop their own digital twins, and other cities such as Amaravati and Singapore are also in the process of creating their own.