# Digital Twins in the Automotive Industry: The Road toward Physical-Digital Convergence
## 3 Digital Twins in Automotive Industry  
The automotive industry has changed dramatically over time as consumer needs grow and new technologies are constantly entering the field. The industry retains some of its traditional infrastructure while being constantly enriched with emerging digital services based on sensors and devices utilizing artificial intelligence, which operate mainly after the product enters the market. The involvement and importance of Digital Twins in the improvement of the vehicle aid in its life cycle-added value and also in the optimized design of future vehicles [49; 50]. Figure 3 depicts a typical Digital Twin arrangement applied in the automotive industry. In order for a vehicle to enter the market, it should undergo a number of obligatory design and control stages. The first stage concerns the initial design of the vehicle's exterior surface in a relevant CAD design software package. At that point, designers start with a simple exterior and interior modeling and then proceed with the design of the vehicle's individual components. Physical prototyping has also evolved nowadays with the introduction of 3D printing technology that allows designers to fabricate physical prototypes of their designs rapidly for testing operations [50; 51; 52; 53; 54; 55]. However, while physical prototyping is essential, the simultaneous presence of a Digital Twin is of paramount importance for the automotive companies. In the initial stages of product development, the Digital Twin can collect the vehicle's behavioral information in performance terms, thus providing valuable information to the designers and system engineers. The continuously increasing number of various components existing and functioning in a car can be a real challenge for the product development team. As it can be very time consuming to actually test each individual system, a Digital Twin can simulate the existence and function of various systems and provide valuable information about their suitability, interoperability, and performance. In this context, and by employing artificial intelligence technology, failure rates can be forecasted, saving a lot of unpredictable expenses [56; 57; 58]. Upon the vehicle's market introduction, in the case of test conduction or a potential recall campaign, via a Digital Twin, vehicle test data can be simulated to determine their quality and performance, such as the use of a new component under various conditions to implement design improvements and to experiment with substantially different elements that may lead to its optimization. Product performance may be predicted along with changes made in real time, determining the optimal configuration. By tracking key components, no recall is required for tens of thousands of products in the event of a problem. Those directly affected can be identified immediately by locating a consignment of corroded components during transport from abroad [59]. Figure 3: A typical Digital Twin arrangement applied in the automotive industry. In the sales field, the digital twin of a vehicle with 3D vehicle reconstruction and visual representation can make a possible buyer alter its color when visiting an automotive manufacturer's site. The same applies to different vehicle aesthetic elements such as the interior, allowing for a customized product tailormade for the customer. In the case of used cars, buyers often have no other option but to speculate about the condition of a vehicle. A used vehicle with digital identity assists with the tracking about its maintenance record with the digital twin containing all relevant data [60; 61]. Digital Twin technology also has great potential in electric vehicles. The modus operandi in this case suggests that an electric vehicle should be linked with its customized digital twin. Via installed IoT sensors on the vehicle, the sensors can exchange data with the vehicle's digital twin.