# Leveraging Digital Twin Technology for Sustainable and Efficient Public Transportation
## 2 Review of Different Aspects of Digital Twins
### Public Transportation and Digital Technologies  
Recent advancements in digital twin technology have significantly impacted public transportation systems, offering promising improvements in efficiency, safety, and operational management. By using simulation platforms enriched with real-world data, autonomous vehicles (AVs) can be tested and trained in a variety of scenarios, which enhances decision-making and safety and accelerates the deployment of self-driving technologies. One study highlights that intelligent expressways, AVs, and ITSs remain the primary focus areas for the application of digital twins in traffic management. While progress has been made with data mining, cloud computing, and other data-processing technologies, the ability to handle and extract useful information from the massive volumes of transportation data still requires further development [20]. In urban settings, digital twins are central to the operation of intelligent traffic management systems [81]. Urban traffic management can benefit from digital twins that model entire urban networks intersection by intersection. By simulating different traffic scenarios, digital twins can analyze road network density and optimize solutions for traffic flow. This ensures more effective management of intersections equipped with numerous traffic sensors. With such systems in place, urban traffic control can automatically adjust and optimize based on real-time data, leading to improved road efficiency, safety, and efficient resource management. In addition to urban streets, digital twins play a key role in the management of smart highways. Intelligent highway systems, which focus on areas such as toll collection, inspection, road condition monitoring, and all-weather access, leverage digital twin technology to process real-time data from vehicle and road sensors. This information is displayed to drivers via high-precision lane-level maps, assisting them in understanding current road conditions and the movement of surrounding vehicles. Moreover, these data are uploaded to a central digital twin platform, enabling traffic managers to issue early warnings and make informed decisions on road safety. The use of digital twin technology in public transportation has the potential to revolutionize the sector [82]. By providing a digital identity for transportation assets, synchronized visualization, and real-time interaction between virtual and physical environments, digital twins enable traffic managers to control traffic perception, determine travel demand, issue road warnings, and coordinate emergency responses. These capabilities improve both safety and operational efficiency, offering new possibilities for intelligent driving and traffic management. A visual representation of a smart transportation platform based on digital twins is presented in Figure 3.  
AVs (autonomous vehicles) and EVs (electric vehicles) have been the focus of recent studies, particularly digital twins, which are used for the development and testing of  
Figure 3: Representation of a smart transportation platform [82]. electric propulsion systems. Regularly powered by electricity, these cars typically have advanced AI or machine learning (ML) technologies, which enable them to detect their environment, plan their routes, and drive safely [21]. Electric propulsion systems, which can be optimized using digital twin models running alongside ML algorithms, not only increase the efficiency of the vehicle but also improve the vehicle's performance. Digital twin networks (DTNs) are also part of the city's public transportation, and they offer updates like the real-time car status and vehicle safety information throughout the city. Therefore, the digital twin network plays a significant part in the development of the whole EV charging infrastructure scenario, as the city mobility undergoes significant changes. The same technology also allows for better understanding and controlling EV public transportation through simulation and feasibility studies as well.