From Simulation to Reality: Safe and Efficient Urban Air Mobility Operations for Istanbul City
ECCO’25 Conference on European Chapter on Combinatorial Optimization , Marrakush, Morocco, 8 - 10 May 2025, pp.1-2, (Summary Text)
- Publication Type: Conference Paper / Summary Text
- City: Marrakush
- Country: Morocco
- Page Numbers: pp.1-2
- Istanbul Kültür University Affiliated: Yes
Abstract
Urban growth in recent years has put pressure on transportation infrastructure, especially in metropolitan areas, leading to negative consequences such as traffic congestion, complex traffic scenarios, delays, and other related issues. Therefore, innovative mobility solutions are needed to guarantee the safety and efficiency of urban transportation. Urban Air Mobility (UAM) is considered as a solution to traffic congestion, and in this context, it is intended to use small, autonomous, low-altitude aircraft to transport passengers or cargo in urban and suburban areas soon. However, the implementation of new urban air transport concepts faces numerous obstacles in terms of safety and security, which are essential for aviation. As the capacity of existing airspace and Air Traffic Management (ATM) systems will be exceeded due to the increasing number of flights, optimizing airspace utilization depends on a safe and reliable system optimization process that minimizes delays, completes flights with minimum fuel consumption and meets future flight demand. The effort to balance demand and capacity is known as Air Traffic Flow Management (ATFM). The overall purpose of ATFM initiatives is to find a compromise solution between all stakeholders, usually based on some criteria of fairness. In other words, a framework is needed that can manage multiple types of drones operating in a crowded, low-altitude urban airspace, taking off from specific locations, navigating a multi-layered air network, and landing at other designated areas. Although drones are expected to be equipped with collision avoidance capabilities, the complexity of operating in congested U-spaces where flights can be disrupted requires multi-layered safety control to minimize potential accidents. Therefore, path planning algorithms should also consider collision avoidance, i.e., operational efficiency is not the only important criterion. This significantly increases the complexity of path planning in UAM operations, as the computational requirements increase exponentially with the number of conflicts between routes.
In this work, we aim to develop a four-dimensional (space-time) urban airspace management concept for UATFM that considers dynamic flow structure, congestion, operational efficiency, and safety. First, we will develop a 3D UAM route network model of the U-space for the city of Istanbul to identify possible routes for each origin-destination (OD) pair in each flight request. In the second stage, we will perform congestion-free demand-capacity optimization for flight demands and determine feasible flight plans. Our model will be based on underutilized paradigms in this field, such as metaheuristics and probabilistic search methods. These algorithms will also cover specific emergency and contingency protocols and conflict-free path planning for security plans. The proposed algorithms will be verified and validated using a simulation tool (Pybullet) that considers six-degrees-of-freedom flight dynamics models and can adapt to different synthetically generated UAM scenarios. Then, to see the applicability of the model to real-life scenarios, the proposed algorithms will also be tested on mini drones (Crazyflie), considering that UAM systems are not yet operational. In extensive experiments, we will analyze the impact of different parameters such as congestion rate, distribution of obstacles and restricted areas on the map, vertical and horizontal separation, and different drone speeds on the safety of UTM operations, especially on the safe landing of a drone in emergency situations. For contingency planning, a set of rules and actions will be entered into the UATFM module, taking into account various unforeseen events, and the resilience of the system in the face of a real crisis will also be tested.