New Tool Simulates Drone Traffic

innovatiONS 8 THE iSCHOOL @ SYRACUSE UNIVERSITY I n the fall of 2017, Associate Professor Carlos Caicedo began work as part of a team building a simulator environment to study air traffic planning and communication resource management for Unmanned Aerial Vehicle (UAV) systems (“drones”). The cross-disciplinary team has since developed a successful prototype of the simulator, and based on that early success, the project is moving into a second phase.

Caicedo, with two faculty members from the School of Engineering and Computer Science at Syracuse University and two doctoral engineering students, first built a prototype agent-based modeling and simulation tool for simulating air traffic capacity scenarios for commercial UAV operations. The platform permitted them to simulate the effects of drone air traffic capacity, and then to test and assess the impact on communication network resources required for effective operation of the drones within that airspace. Their work examined the changing interrelationship of communication between the UAV devices flying within a particular area and the drone operations. In particular, they have assessed what communication resources are necessary to successfully support effective communication between the UAVs and their operators during various situations and levels of drone traffic. The simulator offers a range of configurable parameters that define the different scenarios to be studied, such as the launch rate of UAVs, locations of UAV launch and landing sites, type of missions to be carried out by UAVs (such as package delivery and monitoring), configurable no-fly zones, terrain/ landscape information, communication channel characteristics and communication infrastructure characteristics. “The use of Agent-Based Modeling and Simulation techniques makes this simulator very adaptable and scalable to a range of air traffic and communication network scenarios that can span a city, county, state or larger regions with hundreds to thousands of concurrent air missions,” according to Caicedo.

The project is being jointly funded by Syracuse University’s Center for Advanced Systems and Engineering (CASE), a NYSTAR-designated Center for Advanced Technologyin complex information systems, and the French multinational company Thales. “CENT and CASE in particular, have had extensive experience conducting joint academia/industry projects. We hope our collaboration with Thales continues to be successful and attracts other opportunities,” Caicedo says.

The team hopes to continue a two-year research and development collaboration to explore the use of AI (artificial intelligence) and Deep Neural Network techniques in UAV traffic planning and to address additional wireless communication network resource management and design issues, according to Caicedo. n Caicedo and College of Engineering Team Develop Tool To Simulate Commercial Drone Traffic and Applications

“CENT and CASE in particular have had extensive experience conducting joint academia/industry projects. We hope our collaboration with Thales continues to be successful and attracts other opportunities.” — CARLOS CAICEDO, ASSOCIATE PROFESSOR Carlos Caicedo