The Role of Digital Twins in Connected and Automated Vehicles

Digital twins found their genesis in the halls of NASA and the methods of product lifecycle management. Rapidly evolving trends around the proliferation of sensors, the Internet of Things, Industry 4.0, and cyber-physical systems have spurred the growth of digital twins. This paper reviews digital twins and their use in connected and automated vehicles (CAVs). Strictly speaking, digital twins must have communication between a physical system and its model, as opposed to similar methodologies that achieve indirect communication through iteration, or that substitute different parts of a system simulation with bits of hardware or software for testing. In practice, new methodologies for testing CAVs are sufficiently complex and difficult to apply simple labels. This is seen in our review of vehicular digital twins. Several gaps and challenges are apparent for the continued advancement of digital twin applications. We note some developing areas as traffic management centers, digital maps, onboard diagnostics, and logistics. Digital twins foster model reuse and encourage the use of multiple models at different scales of resolution. The role of digital twins will continue to grow as models become more tightly integrated to the physical systems they represent. This will drive such models towards uniqueness (matching a particular vehicle or road), adaptability (evolving with changing conditions and subject to wear and tear), and interpretability (conveying useful information to a human user). A maturing connected infrastructure and the development of smart cities will cause the number of new digital twin services to explode in a myriad of unforeseen ways.