Drone Supported Delivery Traffic in Urban Vehicular Networks
The current traffic volume in many cities is already a problem that can no longer be solved by expanding the road network. In the context of “Urban Air Mobility” new mobility concepts for airspace are often validated with enormous costs in field tests. Delivery vehicles have a strong influence on the traffic flow due to their long standstill times. This is because the driver manually delivers the parcel to the customer’s apartment and the vehicle blocks parts of the road such that overtaking is often not possible for the following traffic. Even if the standstill time is short, the constant acceleration and deceleration causes high emissions and fuel consumption as well as costs due to abrasions.
Delivery drones offer an alternative to traditional delivery traffic because they don’t affect road traffic. However, using drones would raise additional problems and questions that need to be resolved in advance.
Goals of the thesis
In this thesis, we want to investigate the impact if drones are taking over part of the parcel delivery process. To give an example, it is unclear from where drones should start the delivery process. If drones only start from a parcel station in the city center, this also means that a truck must continue to commute to the city center in order to place all parcels at a central location. As another example, the truck could place all parcels next to a freeway ramp, but then a drone has to travel longer distances. Building on Veins, an open-source vehicular network simulation framework that can simulate wireless networks of cars, and inet, an open-source model suite for the OMNeT++ discrete event simulator, the thesis will analyze the implications of different design strategies for drone delivery services in urban areas. All strategies are evaluated by different metrics that describe the impact on the road traffic, but also the impact on drone properties.
C++, Network Simulation, Drones
 W. Shi, H. Zhou, J. Li, W. Xu, N. Zhang, and X. Shen, “Drone Assisted Vehicular Networks: Architecture, Challenges and Opportunities,” IEEE Network, vol. 32, no. 3, pp. 130–137, May 2018. https://doi.org/10.1109/MNET.2017.1700206.
 M. Mozaffari, W. Saad, M. Bennis, Y. Nam and M. Debbah, “A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems,” in IEEE Communications Surveys & Tutorials, vol. 21, no. 3, pp. 2334-2360, 2019. https://doi.org/10.1109/COMST.2019.2902862