# Leveraging Digital Twin Technology for Sustainable and Efficient Public Transportation
## 2 Review of Different Aspects of Digital Twins
### Current Applications of Digital Twins in Public Bus Transportation  
#### 2.3.1 Fleet Management  
Bus fleet management, when originally termed in the 1970s, primarily focused on the maintenance of fleets. Currently, fleet management is associated more with efficient routing and scheduling (operational), location tracking and accident detection (safety), and real-time decision-making communication to fleet operators. It is also concerned with asset management (energy efficiency), a longer and reliable service life, and overall sustainability [83]. Fleet management heavily relied on manual record-keeping and radio communication. Telematics systems and Global Positioning Systems were responsible for providing the precise locations of buses. Fleet management software was introduced to schedule maintenance, keep track of fuel consumption, and manage driver logs. More recently, Radio Frequency Identification (RFID) and the Internet of Things (IoT) have been implemented, whereby real-time tracking, inventory management, and decision-making have become more successful when using advanced data analytics [84]. Digital twins have also been used to improve fleet operations by prioritizing predictive maintenance, fuel efficiency, and asset management. For instance, one study noted the integration of high-fidelity simulations with on-board health management systems, maintenance history, and historical data of vehicles to point out the benefits of DTs [10]. The authors use multidisciplinary physics-based simulations to develop models and methodologies that are essential for certification and ensuring the life-cycle sustainability of vehicles. Concepts like real-time prediction of composite structures, sensitivity to microcracks, and dielectric spectroscopy were studied to measure material change properties and determine the durability of materials and predict degradation and failure [85]. There was also a study conducted to reduce the operation and maintenance costs of fleets by improving electrified bus energy efficiency at the fleet level through digitalization. The optimal operation performance for all bus routes was determined via dynamic programming. The goal was to improve energy efficiency and management by processing large volumes of data produced by bus fleets. Moreover, simulation including real-world conditions such as traffic congestion, passenger variations, and auxiliary loads (air conditioning and light usage, driving motors) was also performed to determine the optimal operation, resulting in efficient fuel consumption by using dynamic programming. Fuel and grid cost calculations were evaluated to develop an economic model for fleet learning. Lower fuel consumption was observed, with fleet energy efficiency increasing by up to 46%, and fuel consumption decreasing by almost 49% when compared to historical data [37]. Another paper evaluated the electrification of public transportation as a sustainable mobility solution to address environmental concerns and improve public transportation systems. Raising concerns of trust and security, a blockchain-based system was proposed for fleet management and managing the charging of electric buses to address these challenges. Timely fleet schedules are proposed to be conducted at the least charging costs by analyzing the Quito-Ecuador bus fleet charging [86]. In a study conducted to determine the usage of alternative operation of fleets, researchers assessed future scenarios of municipal vehicles composed of alternatively powered vehicle types compared to the traditional fleet. It was found that the change to alternative fuel vehicles (battery and fuel cells) requires changes in the existing infrastructure. By analyzing existing conditions for fleet composition and infrastructure, the authors pointed out challenges such as developing new refueling concepts and facilities to accommodate different types of fuels. However, the authors pointed out that these complex logistical and financial undertakings can be assessed and simulated by developing digital twins.