## 3 Emerging and State-of-the-Art Technologies
### On Digital Twins and Communications
In cities like San Francisco and Singapore, AVs are already in operation by companies like Waymo [223], Cruise [224], and A*STAR [225], Aptiv [226], and MooVita [227], respectively. Establishing intelligent networks that integrate AVs with conventional vehicles is essential for ensuring safe andefficient transportation. It is well-understood that the realization of a large-scale human-machine ecosystem within cities is not feasible without such networks. A DT model, continuously updated with real-time data from various cities and driving conditions, can make decisions with near-zero statistical error, guiding autonomous navigation in real-world environments. For example, a DT-powered system can make critical decisions regarding (a) when a vehicle is to stop, accelerate, or decelerate, (b) how to safely overtake another vehicle, (c) how to avoid collisions with vehicles or pedestrians, and (d) decision making in high-risk scenarios, such as choosing between colliding with another vehicle or risking harm to a pedestrian. By continuously learning from real-world driving scenarios, we believe that a living DT network will be instrumental in improving safety, efficiency, and decision-making autonomy in AVs. A similar, but even more complex, application of DTs is in unmanned aerial vehicle (UAV) navigation, particularly in commercial drone delivery services. Companies such as Amazon, DHL, FedEx, and Zipline are already using drones for logistics, including medical supply transport, package delivery, and food distribution, e.g., [228]. For example, (a) Meituan, a Chinese company, has 30 drone delivery routes, handling over 300,000 orders [229], (b) Amazon operates drone delivery services in College Station, Texas, and Phoenix, Arizona [230], and (c) food delivery by drones is now part of daily life in Shenzhen, China [231]. Notably, the drone package delivery market is projected to reach 8.57 billion USD by 2032 [232]. Therefore, it is expected that in the near future, thousands of drones will be deployed for last-mile deliveries [233], creating an extremely complex air traffic management challenge. It is these authors' position that traditional human-controlled air traffic systems will not be able to scale for managing these thousands of drones. Current aviation accident data indicate that 69% of general aviation accidents are due to pilot error [234]. Therefore, the DT-powered UAV navigation systems takeover is expected, with the goal to dramatically improve safety by reducing human intervention and optimizing flight paths in real-time. Moreover, in highly populated cities, where spectrum congestion is already a major issue, drones are required to be able to efficiently communicate with base stations. Currently, FCC regulations restrict drone operations to unlicensed frequency bands, including 2.4 GHz, 5.8 GHz, 900 MHz, and 433 MHz [235]. If these regulations pertain, a DT engine is expected to dynamically allocate spectrum, optimize routing, and ensure robust, interference-free communications in these environments. Additionally, as data demand continues to skyrocket, traditional communication networks will struggle to process massive amounts of real-time information from these thousands UAVs as well as other autonomous systems connected to the same communication network. We expect DTs to alleviate this challenge by training machine learning models for predicting, optimizing, and guiding device performance, thus improving overall network performance. As expected, security and privacy are critical concerns in communication systems. Malicious users may attempt to intercept data, manipulate control signals, or disrupt information. A DT-enhanced security framework can address these challenges by improving (a) precoding schemes for secure transmission, (b) cooperative secure communication strategies, (c) the mitigation of pilot contamination, (d) robustness against hardware impairments, and (e) energy-efficient communication. Finally, we expect DT to revolutionize hardware development.