# Evaluating the Impact of Drone Signaling in Crosswalk Scenario
## 1 Introduction  
Unmanned Aerial Vehicles (UAV) are used today in a large number of daily life applications [1]. In fact, since the beginning of the 2010s, UAV are being introduced to improve the road traffic efficiency [2]. In addition, the interest to Cooperative Intelligent Transportation Systems (C-ITS) has risen in recent years, especially in the context of smart cities [3]. Several works and research projects identified multiple scenarios for the application of UAVs in these environments [4]. In C-ITS, where autonomous vehicles interact, road safety is a complex research problem, especially when Vulnerable Road Users (VRU) are involved. Currently, the use of UAVs in urban areas is not yet authorized in most countries in the world (see Reference [5] for more details about local UAV regulations). In the white paper by Reference [6], the authors have shown how and why various regulations and requirements influence the use of radio in drones. They focused on data link reliability for professional drone use by providing the technical background and links to where such regulatory ruling can be found, focusing in the U.S. and some countries in Europe. Despite this restrictive legal context, various recent works have shown the benefits of UAV technologies to improve efficiency and safety in urban areas. In most of theseapplications, UAVs have a certain level of intelligence, which allows them to be used as high-performance sensors, information collectors, or even as communication relays, particularly when land cover is not sufficient [7; 8]. The advances of C-ITS technologies and the interesting properties of UAVs provide a favorable context to introduce a UAV in a use case where we consider a conflict involving a car and a pedestrian. In this work, UAV is expected to control the situation, collect information, and send instructions to the car driver in a case of harmful situation in order to avoid collision between the car and the pedestrian. For this, we take into account two cases: in the first, case the car arrives to the crosswalk through a straight line; in the second case, the car approaches the crosswalk through a curved trajectory. The UAV is likely to detect the presence of the pedestrian before the latter becomes in the Visual Line Of Sight (VLOS) of the terrestrial vehicle. Hence, the UAV can send the information earlier to the driver, and this is likely to provide an earlier reaction of the car driver. If we assume that the driver is cooperative, he will adapt his behavior based on the messages received from the UAV. In these conditions, the UAV signaling contributes to reduce both accident rate, braking distance, and energy consumption. In addition, the UAV improves occasional visibility reduction. To this end, the rest of the paper is organized as follows. In Section 2, we detail related works and state-of-the-art. In Section 3, we present the studied scenario, as well as our proposed algorithm, the made hypotheses, and the chosen simulation parameters. Then, in Section 4, we present the simulations results and associated analysis to finally discuss these results in relation to the national statistics in accidentology in France in Section 5. Section 6 is, lastly, dedicated to summarize the main conclusions and further work.