# Leveraging Digital Twin Technology for Sustainable and Efficient Public Transportation
## 2 Review of Different Aspects of Digital Twins  
### Digital Twins in Urban Infrastructure  
A digital twin is a virtual representation of a physical system or process that integrates data in real time, using simulations and applying artificial intelligence to optimize performance [15]. The concept was introduced in the National Aeronautics and Space Administration (NASA) in the 1960s where the scientists developed a \"living model\" for conducting Apollo missions [16]. Their version of the digital twin was used in processing data to model events, aid in forensic analysis, and support future decision-making. \begin{table}
\begin{tabular}{c c c c} \hline
**No.** & **Theme of Paper** & **Citation Number** & **Summary** \\ \hline
4 &
\begin{tabular}{c} Traffic Data \\ Management, \\ Vehicular Network \\ and Architecture \\ \end{tabular} & [28; 48; 49; 50; 57; 60; 66; 68; 69; 70; 71; 72; 80] & Research studies explore the application of DTs in traffic data management, vehicular networks, and transportation infrastructural architecture [28; 48; 60]. Several studies discuss data-driven approaches for real-time traffic optimization, using DT models to analyze congestion patterns and predict traffic flows [49; 50; 66; 68; 69; 70; 73; 74; 75; 76; 80]. Other studies highlight the significance of vehicular networks for V2X communication and intelligent transport protocols that enhance road safety and efficiency [77; 78; 79; 71; 72; 71]. Studies also investigate the challenges of integrating DT technology into the existing transportation architecture, including scalability, interoperability, and real-time data-processing [28; 48; 57; 67]. \\ \hline
5 &
\begin{tabular}{c} Predictive Analytics \\ and Simulation \\ \end{tabular} & [17; 18; 34; 36; 49; 54; 55; 72; 81; 102] & Studies discuss DTs in predictive analytics and simulation techniques in public transportation and urban mobility [18; 34; 72; 85; 94; 99]. Some studies explore the use of DT models for demand forecasting and to optimize fleet management and help planners enhance scheduling efficiency [36; 49; 82; 84; 86; 88; 89]. Other studies develop simulation-based methodologies to test infrastructural projects for risk-free experimentation and validation of new transit policies before implementation [17; 54; 55; 87; 95; 101; 102]. Papers also focus on the predictive capabilities of DTs in reducing operational uncertainties, estimating vehicle performance, and improving the overall passenger experience [35; 82; 83; 90; 91; 92; 93; 97; 98; 100]. \\ \hline
6 &
\begin{tabular}{c} Resilience and Risk \\ Management \\ \end{tabular} & [24; 31; 59; 60; 79; 99; 103; 104; 105; 103; 106; 103; 107; 108] \\ \end{tabular}
\end{table} 
Table 2: _Cont._Recently, the digital twin has gained popularity in many areas of research since it can work as a virtual mirror of a physical system. This enables real-time synchronization with sensor data from the field (real world). This synchronization allows better decision-making and systems to carry out necessary actions in an optimized manner [17]. Hence, while working with a huge amount of data that are continuously generated within automated systems, digital twins enhance productivity by improving quality objectives and thus enable further automation [18]. The role of a digital twin in the age of smart cities is paramount, with data gathered through various electronic methods and sensors. A smart city may be viewed as using information and communication technologies to achieve better public services, based on comfort, maintenance, and sustainability concerns. By integrating the Internet of Things, 5G wireless systems, blockchain, co-computing, simulation, and artificial intelligence, a digital twin could revolutionize urban governance. In urban transportation, for example, there has been a revolutionary turn of events due to rapid advancements in the aforementioned technologies. This interconnectedness has allowed a digital twin to virtually simulate the interactions between people, vehicles, roads, and environments.