BB-Planner: an urban traffic dataset generation tool

Abstract

There has been heightened interest in the application of unmanned aircraft operations to urban environments in recent years. This has triggered activities both in the research communities and private sector to analyze the extent to which safe, secure and efficient operations can be performed. However, there is an acute lack of reliable data in this field. BB-Planners aims to help alleviate this issue. BB-Planner is a simulation tool developed during the BUBBLES project, funded by the SESAR Joint Undertaking (SJU), and it is focused on the generation and analysis of drone traffic in an urban environment. This software is able to generate trajectories with different patterns of flight that simulate several types of missions that could occur in an urban setting, including delivery, surveillance and inspection. These trajectories can be randomly generated or deconflicted trajectories defined by their waypoints or areas of operation. The trajectories generated at this stage are considered ideal, however, for different applications the degradation generated by the surveillance system has to be considered. Thus, the BB-planner tool can inject this degradation, considering the positional errors, the latency and the probability of detection of the surveillance system. After the drone trajectories are generated, the system can count the number of conflicts that occurred during the simulation. For this end, the value used for the separation minima can be a single value for all the current drones provided by the user and based on the total system error (TSE) or a different value for each drone based both on the TSE and the performance characteristics of the aircraft. BB-planner can be used to generate datasets that approximate an airspace with different operators and evaluate the different parameters’ effect on the frequency of conflict and other relevant metrics.