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In 2022, FIXAR becomes a partner of the project Urban Air Traffic Management Development & Demonstration, led by Istanbul Kultur University Technology Transfer Office.
The main goal of the project is to bring together experts from state, business and education sectors to propose the urban air traffic management (UATM) system to develop and deploy solutions for the mobility needs of people and businesses, including the delivery of goods, waste collection, and transport with the aim to facilitate, improve and even solve air quality and congestion problems, and create long-standing impact on cities and urban life quality.
In this project, FIXAR is working together with the project’s technical team and providing the full-stack drone solution for flight and system integration, as to demonstrate real time examples of possible solutions. FIXAR also takes the role of a lead commercialization partner for RIS (Regional Innovation Scheme) innovation project.
“FIXAR team is pleased and honored to take part in a project that is covering highly relevant subject for the unmanned aerial vehicle industry. We see that management systems for the low airspace traffic are necessary and fundamental as drones are becoming more accessible and the number of users increase. As drone applications continue to expand and improve, we expect a continuous increase of the aircrafts amount in the low airspace,” Yulia Druzhnikova, co-founder and director of global expansion at FIXAR.
“It is inevitable for urban traffic management to make the shift from the current human-controlled system to an autonomous system on urban airspace and this way enabling the capacity to open the airspace to a large number of users. Therefore, we are looking to develop an automated UATM system targeting urban air mobility which is a specific area of future mobility,” Alparslan Güzey, deputy director and project Manager at Istanbul Kultur University Technology Transfer Office.
The system will be using innovative operational research algorithms developed by the project partners and evaluation of the effectiveness of the algorithm will be demonstrated through real-time simulations and drone flight demonstrations.