One of the most challenging problems during disasters involving crowds is pedestrian evacuation. It is very important in such situations to improve survival rates by getting all or most of the people out in the shortest possible time. Technological intervention through augmenting the evacuation process using an unmanned aerial vehicle (UAV) exhibits great potential in improving survival rates, but the exploration of this method is still in its infancy. Therefore, this study explores the potential of utilizing UAVs for crowd management during emergency evacuations. We conducted a rigorous study, using a simulation model featuring four UAVs and differing numbers of pedestrians, with use of two UAV guidance approaches: partial guidance and full guidance. The experimental results suggest that exploiting UAVs in crowd evacuation and following the partial guidance approach can lead to a more efficient evacuation process.

No abstract

With the high demand for using location-based services (LBSs) in our daily lives, the privacy protection of users' trajectories has become a major concern. When users utilise LBSs, their location and trajectory information may expose their identities in continuous LBSs. Using the spatial and temporal correspondences on users' trajectories, adversaries can easily gather their private information. Using collaboration between users instead of location service providers (LSPs) reduces the chance of revealing private information to adversaries. However, there is an assumption of a trusting relationship between peers. In this paper, we propose a trustworthy collaborative trajectory privacy (TCTP) scheme, which anonymises users' trajectories and resolves the untrustworthy relationship between users based on peer-to-region LBSs. Moreover, the TCTP scheme provides query content preservation based on a fake query concept in which we conceal the user's actual query among a set of queries. The results of several experiments with different conditions confirm that our proposed scheme can protect users' trajectory privacy successfully in a trustworthy and efficient manner.