Unmanned Aerial Vehicles (UAVs) are becoming an attractive solution for road traffic monitoring because of their mobility, low cost, and broad view range. Up to now, existing traffic monitoring systems based on UAVs only use one UAV with fixed trajectory to extract information about vehicles. In this paper, we propose a road traffic monitoring system using multiple UAVs. We develop a method to generate adaptive UAVs trajectories, which is based on the tracking of moving points in the UAV field of view. Also we generate UAVs trajectories using mobility models that are usually used to model vehicles mobility. UAVs monitor the traffic on a city road, they are responsible for collecting and sending, in real time, vehicle information to a traffic processing center for traffic regulation purposes. We show that the performance of our system is better than the performance of the fixed UAV trajectory traffic monitoring system in terms of coverage rates and events detection rates.

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This paper provides a description of a wireless mesh network testbed setup and a measurement-based performance evaluation of the Optimized Link State Routing (OLSR) protocol [7] under three different routing metrics. The considered metrics include hop-count, ETX and ETT. The network performances are evaluated in an indoor testbed formed by heterogeneous MIMO devices. A part of our tests was about the impact of 802.11n features on the network performances showing the importance of lower layers consideration. Our measurements point out the shortcoming of each metric and eventual optimizations towards a more efficient routing. Experimental results show that OLSR-ETT outperforms OLSR-ETX and OLSR-hopcount significantly in terms of packet loss, end-to-end delay, and efficiency.

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