Aerial Surveillance in Cities: When UAVs Take Public Transportation Vehicles

Abstract

This paper considers using unmanned aerial vehicles (UAVs) to survey important sites across a city. When the sites are relatively far from the UAVs’ depot, the UAVs may not be able to reach many of the sites. Suppose that a UAV can take public transportation vehicles (PTVs) like a passenger. Then, it may reach a site that is unreachable by flying only. Based on this UAV-PTV scheme, we investigate a task-UAV assignment problem, which assigns a set of surveillance tasks to UAVs. We formulate a mixed-integer linear programming (MILP) problem that minimizes the overall energy consumption of UAVs, subject to that every site is surveyed by a certain number of UAVs during a given time window, and all UAVs successfully return to the depot. Considering that this problem is NP-hard, we present two sub-optimal solutions. The first solution orders the surveillance tasks according to the starting times of their time windows. Then, starting from the earliest one, it assigns the tasks one by one to UAVs. The second solution breaks the tasks into small non-overlapping groups. It then assigns tasks to UAVs group by group. The former solution quickly addresses the assignment problem, but it lacks the overall management of UAV resources. The latter improves this by assigning a group of tasks simultaneously, and it can control the computation complexity by limiting the group size. The comparison with the brute force method shows that the proposed solutions can achieve competitive performance in a reasonable time. Note to Practitioners—Unmanned aerial vehicles (UAVs) have been widely used in surveillance missions. However, one challenge practitioners often meet is the limited flight duration. Commercial UAVs are in general powered by the onboard battery. Due to the restriction of payload, the battery capacity is constrained, which limits the UAVs’ operation time. In this paper, we present the approach exploiting public transportation vehicles (PTVs). In our design, a UAV can take a public transportation vehicles such as buses, trams and trains on the roof and transfer between vehicles when necessary. With this UAV-PTV collaboration scheme, we consider how to efficiently assign surveillance tasks to UAVs. Due to the NP-hardness of the considered problem, two suboptimal algorithms are presented.