The integration of small-scale Unmanned Aerial Vehicles (UAVs) into Intelligent Transportation Systems (ITSs) will empower novel smart-city applications and services. After the unforeseen outbreak of the COVID-19 pandemic, the public demand for delivery services has multiplied. Mobile robotic systems inherently offer the potential for minimizing the amount of direct human-to-human interactions with the parcel delivery process. The proposed system-of-systems consists of various complex aspects such as assigning and distributing delivery jobs, establishing and maintaining reliable communication links between the vehicles, as well as path planning and mobility control. In this paper, we apply a system-level perspective for identifying key challenges and promising solution approaches for modeling, analysis, and optimization of UAV-aided parcel delivery. We present a system-of-systems model for UAV-assisted parcel delivery to cope with higher capacity requirements induced by the COVID-19. To demonstrate the benefits of hybrid vehicular delivery, we present a case study focusing on the prioritization of time-critical deliveries such as medical goods. The results further confirm that the capacity of traditional delivery fleets can be upgraded with drone usage. Furthermore, we observe that the delay incurred by prioritizing time-critical deliveries can be compensated with drone deployment. Finally, centralized and decentralized communication approaches for data transmission inside hybrid delivery fleets are compared.

翻译：将小型无人驾驶航空飞行器(无人驾驶飞行器)纳入智能运输系统将赋予新的智能城市应用和服务能力。在未预见到的COVID-19大流行爆发后,公众对交付服务的需求成倍增长。移动机器人系统本身就有可能最大限度地减少与包裹交付过程的直接人与人之间的直接互动。拟议的系统系统包括各种复杂方面,如分配和分配交付工作、建立和维持车辆之间的可靠通信联系以及道路规划和流动控制。在本文件中,我们采用了系统层面的观点,以确定对UAVD-19大流行的建模、分析和优化提供UAV辅助包裹交付的关键性挑战和有希望的解决办法。我们提出了一套系统模型,用于UAVD-辅助包裹交付,以应对COVID-19大宗交付过程引起的更高的能力需求。为了展示混合交付的好处,我们提出了一份案例研究,重点是确定车辆交付时间紧迫的优先顺序,如医疗货物。我们进一步证实,传统交付车队的能力可以与无人驾驶飞机进行建模、分析和优化解决方案的交付方式。最后,我们观察到,通过分散的交付方式,可以将交付的数据与核心运输方式进行升级。