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The current push in automation, communication, and electrical energy storage technologies has the potential to lift urban mobility into the sky. As several urban air mobility (UAM) concepts are conceivable, all relevant physical effects as well as mutual interrelations of the UAM system have to be addressed and evaluated at a sufficient level of fi...
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... Improving the efficiency of long-distance transportation is critical for urban transport planning. Technological advancements in air mobility offer a promising pathway for developing three-dimensional urban transportation to enhance travel efficiency [2][3][4][5]. In 2016, Uber Elevate published a white paper on urban air mobility (UAM) and urban air taxis [6]. ...
The corridor network serves as an effective solution for the airspace structure safety design of UAM. However, current studies rarely account for the ground risk posed by the corridor operation and typically consider a single design objective with limited variables. In this paper, we address these gaps by considering three key factors: demand, safety, and implementation costs. The corridor network design is formulated as a multi-objective optimization problem. In practice, firstly, we define the travel time-saving rate, average population density, and total length of corridors as optimization objectives. Then, we propose a straightforward and efficient corridor network encoding scheme that supports a variable number of corridors, significantly enhancing the diversity and flexibility of corridor network designs. Finally, based on this encoding scheme, we solve the corridor network problem using the unified non-dominated sorting genetic algorithm III (U-NSGA-III). Based on a detailed analysis of the obtained Pareto front, a relatively optimal design scheme across three optimization objectives is determined. The case study conducted in Chengdu illustrates that the corridor network obtained by our method not only achieves a 37.8% reduction in ground risk and a 69.9% decrease in implementation costs, but also saves a comparable 4.7% in time relative to traditional methods.
... To achieve this holistic modelling, the authors of this work chose to collaborate to bring together the higher fidelity models of the different domains into a single modelling environment upon which further studies can be performed. A first collaborative approach with various disciplines has been presented by [15], taking a serial integration approach of the disciplines. In this study, a parallel integration approach is taken to the integration of the disciplines into an agent-based simulation. ...
The implementation of urban air mobility represents a complex challenge in aviation due to the high degree of innovation required across various domains to realize it. From the use of advanced aircraft powered by novel technologies, the management of the airspace to enable high density operations, to the operation of vertiports serving as a start and end point of the flights, urban air mobility paradigm necessitates significant innovation in many aspects of civil aviation as we know it today. To understand and assess the many facets of this new paradigm, a collaborative simulation is developed to holistically evaluate the system of systems through the modeling of the stakeholders and their interactions as per the envisioned concept of operations. To this end, models of vertiport air-side operations, unmanned/manned airspace management, demand estimation and passenger mode choice, vehicle operator cost and revenues, vehicle design, and fleet management are brought together into a system of systems simulation of urban air mobility. Through collaboration, higher fidelity models of each domain can be integrated into a single environment achieving fidelity levels not easily achievable otherwise. Furthermore, the integration enables the capture of cross-domain effects and allows domain-specific studies to be evaluated at a holistic level. This work demonstrates the collaborative simulation and the process of building it through the integration of several geographically distributed tools into an agent-based simulation without the need for sharing code.
... As an extension of the SoS, the GBI and its interfaces can be described using the Feedback-loop Method by Ploetner et al. [19]. Niklaß et al. expand this approach as Cause-Effect Relationships (CER), arranging each subsystem diagonally, allowing for forward and backward iteration loops [20]. This modularizes Ploetner et al.'s approach, enabling expandability and universality within the method application. ...
Advanced Air Mobility (AAM) addresses future transportation challenges by extending networks into the air, helping cities like Hamburg overcome infrastructural limitations. Ground-based infrastructures (GBIs) are crucial for integrating AAM, connecting air and ground transport through subsystems like landing areas, gates, and terminals, tailored to local demands. Our previous work identified necessary GBI subsystems and modeling methods, using scenario techniques to understand influences and constraints in mission planning, topology, maintenance, repair, and energy management. This paper details a simulation-based analysis of GBIs, emphasizing topologies, maintenance, and energy management interactions. AAM is modeled as a complex optimization problem within a simulation environment, using scenario analysis to set parameters and objectives. Network optimization aims to strategically plan local capacities for parking, charging infrastructure, and traffic flows, improving fleet operations. Infrastructure design integrates air and ground systems for VTOL vehicles, with key performance indicators and the Vertiport Design Problem optimizing topology. Maintenance, Repair, and Overhaul (MRO) Ports are designed to be demand-responsive, integrating ground-based infrastructure and mission management systems. Energy management systems consider energy requirements, charging power, range, state of charge, and electrical grid use. MATLAB Simulink models estimate drone energy demand across various scenarios. Subsystem interactions are defined in a workflow for overall system simulation, divided into sub-workflows, exploring synergy effects between parameters.
... UAM will be faced with more complex integrated operation scenarios involving manned and unmanned vehicles in terms of traffic rules and operational control. UAM traffic rules must be innovated and remain compatible with existing air traffic regulations [53]. A high-bandwidth communication system will allow UAM operational control to move in the direction of autonomous decision-making and self-piloting based on air-ground coordinates. ...
Over the past few years, our traditional ground-based transportation system has encountered various challenges, including overuse, traffic congestion, growing urban populations, high infrastructure costs, and disorganization. Unmanned aerial vehicles, commonly referred to as drones, have significantly impacted aerial communication in both the academic and industrial sectors. Therefore, researchers and scientists from the aviation and automotive industries have collaborated to create an innovative air transport system that solves traditional transport problems. In the coming years, urban air mobility (UAM) is expected to become an emerging air transportation system that enables on-demand air travel. UAM is also anticipated to offer more environmentally friendly, cost-effective, and faster modes of transportation than ground-based alternatives. Owing to the unique characteristics of personal air vehicles, ensuring reliable communication and maintaining proper safety and security, air traffic management, collision detection, path planning, and highly accurate localization and navigation have become increasingly complex. This article provides an extensive literature review of recent technologies to address the challenges UAM faces. First, we present UAM communication requirements in terms of coverage, data rate, latency, spectrum efficiency , networking, and computing capabilities. Subsequently, we identify the potential key technological enablers to meet these requirements and overcome their challenges. Finally, we discuss open research issues, challenges, and future research directions for UAM deployment.
... The ultimate vision is a highly connected, efficient, and resilient urban and regional air transport system that contributes positively to society (Hill et al. 2020). The successful implementation of AAM will require a multi-disciplinary approach, bringing together expertise from aerospace engineering, artificial intelligence, electrical engineering, urban planning, policymaking, and others (Niklaß et al. 2020). ...
... Additionally, the literature indicates the need for international harmonization of regulations (Pagallo and Bassi 2020) and inclusive and participatory regulatory processes (Niklaß et al. 2020). ...
Advanced air mobility (AAM) is an emerging field that envisions highly automated, high-tempo, passenger-carrying aircraft operating in urban environments. Numerous stakeholders have emerged in this space, each proposing unique concepts of operation (CONOPS). While this technology will enable a revolutionary leap in modern transportation, many challenges remain unaddressed. Discrepancies exist between envisioned AAM operations, current technology, and outdated federal regulations. This has led to an unclear vision within the industry of the current maturity level of technology and the path of development needed to achieve proposed CONOPS. We seek to fill this gap by integrating multiple proposed conceptual systems into a single, unified path forward for the field. The literature on AAM covers a diverse array of interconnected themes, each containing a multitude of considerations that require extensive exploration and understanding. In the present work, a literature integration was conducted to collate the numerous proposed concepts and envisioned works that exist within the AAM literature. With this information, a comprehensive AAM taxonomy was created to represent this integration of concepts and rectify the inconsistencies within industry CONOPS. This taxonomy will assist future stakeholders in navigating this intricate field while contributing to the safe and efficient development and deployment of AAM.
... For the purpose of this section two definitions are introduced: a "promising location" as a general area with potential for UAM services (with a maximum radius of a few hundred meters); and a "suitable site" as the physical surface for a vertiport (e.g. a rooftop or vacant land). Various studies use geographic information system (GIS)-based approaches to identify promising locations, but these typically fall short of identifying suitable sites [101,102,103,104,105,106,107]. Simultaneously, a range of suitable sites has been suggested in the research community, while not applying it to concrete locations [100,108,23,54,109]. ...
... A collaborative simulation approach is proposed by [104], in order to analyze a UAM network inside the metropolitan area of Hamburg (Germany). It follows the objective of defining low-fidelity analysis components such as demand, vertiport design, vertiport integration, routing, scheduling and setting them into relation in order to analyze interdependencies. ...
... Early contributions of [131] on the ratio between gates and pads have found the ratio to strongly depend on the turnaround time at the gates, which in turn depends on passenger boarding and vehicle charging. Ratios that are being put forth range from 2 to 8 gates per pad [104,132] and are therefore a novelty compared to today's heliports operations, which concerns itself almost exclusively with pad operations. Most publications place all elements on a two dimensional plane. ...
Urban air mobility (UAM) is a new transportation concept made possible by electrification and automation. It has the potential to become an established mode of transport and enrich the existing transportation system. This could be similar to past revolutions caused by the automobile in the 1910s or the airplane in the 1950s. UAM’s validity hinges on fast travel with time advantages over ground-bound modes of transport. Along the chain of travel, processing passengers and vehicles at vertiports is the strongest driver of travel time savings — more than access and egress or cruise speed. Also, vertiports have been identified as a key factor in introduction and scaling of UAM. Therefore, this thesis studies the design and
operations of vertiports, a central contribution towards realizing UAM services in the coming decade. The contribution of this thesis is two-fold with the focus on the latter: vertiport layout design and vertiport airfield operations.
Vertiport design is studied through mixed-integer programming implemented in MATLAB. The central object of research is the relationship between available area for the vertiport airfield and the possible throughput. For this purpose, four geometric topologies are considered: single-pad, satellite, linear and pier. Various prominent vehicle designs (e.g. Joby S4, VoloCity, Lilium Jet) are studied under varying circumstances (e.g. turnaround time at the gate). The studies indicate that vertiport airfields need somewhere between 25 − 350m2 per passenger throughput per hour. Study results are tabulated in detail as well as presented in aggregated form as a rule-of-thumb to allow for first-order vertiport design without having access to the simulation.
Vertiport operations are studied through agent-based modeling and simulation implemented as objectoriented programming in Python. The model consists of pads, gates and stands, which are all connected by taxi-lanes and an interface to the airspace and the passenger terminal. The parameter values of the model were specified through an expert interview series and after iterative refinement the current model contains 20 parameters. With over 1,000 scenario simulations, it was possible to identify and quantify six drivers of operations: (1) peak-hour demand, (2) maximum imbalance between arrivals and departures, (3) number of pads, (4) number of gates, (5) approach and departure time and (6) boarding and de-boarding time. For example, the baseline scenario consists of 4 pads and 12 gates, has a 45 s approach/departure time and a 95 s boarding time. With a requirement of no more than 4 minutes average delay it can cater a maximum of 264 passenger per hour and buffer an accumulated imbalance of 33. It was shown that these six characteristics are sufficient to allow for a reasonably accurate prediction of operational efficiency (i.e. average delay). The final step in this thesis is a synthesis of operational insights into a vertiport design heuristic, which displays the interchangeability of the mentioned drivers of operations.
Further contributions of this work are a systematic literature review of vertiport design and operations in scientific literature and regulatory reports and a top-level study of vertiport networks, promising locations and suitable sites.
The results of this thesis are applicable both in academia and industry. First and foremost, the identified drivers of vertiport operations can inform future detailed research and help address inefficiencies in the envisioned UAM system. Second, the vertiport design heuristic is a simple but powerful tool to be used in preliminary airfield design. Third, rules-of-thumb for vertiport throughput present a metric to compare vehicle designs according to their ground performance. Lastly, this thesis and the attached literature review on vertiports gives a comprehensive overview of the current state of research.
... II. RELATED WORK AAM network simulation research spans diverse methodologies, from analyzing eVTOL energy constraints to comparing air taxis with traditional taxicabs, and integrating traffic simulations to evaluate urban impacts [7]- [9]. Additionally, research has explored the potential shift in commuter demand towards AAM, factoring in travel time savings and vertiport transfer times [11], and employed collaborative system-of-systems modeling to optimize AAM operations covering demand forecasting, vertiport design, and air traffic management [10], [12]. ...
Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks. This paper presents a simulation-optimization framework that dynamically integrates wind variability into AAM operations. We employ a nonlinear charging model within a multi-vertiport environment to optimize fleet size and scheduling. Our framework assesses the impact of wind on operational parameters, providing strategies to enhance the resilience of AAM ecosystems. The results demonstrate that wind conditions exert significant influence on fleet size even for short-distance flights, their impact on fleet size and energy requirements becomes more pronounced over longer distances. Efficient management of fleet size and charging policies, particularly for long-distance networks, is needed to accommodate the variability of wind conditions effectively.
... Szenarioentwicklung umfasst somit die Anwendung unterschiedlicher qualitativer und quantitativer Methoden zur Diskussion von Entwicklungen in einem definierten Zeithorizont. Insbesondere die Betrachtung lokal-räumlicher Eigenschaften mit Hinblick auf gesellschaftliche, topographische und infrastrukturelle Elemente ist hierbei von Relevanz, um die Projektion auf unterschiedliche Anwendungsräume zu ermöglichen Niklaß et al., 2020 ...
Der Abstractband beinhaltet Abstracts zu den Vorträgen, die am 27. April 2023 im Rahmen der Tagung "Nachhaltigkeit Urbaner Luftmobilität" an der Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg gehalten wurden. Die Tagung wurde im Rahmen des Projektes "i-LUM" ("innovative luftgestützte urbane Mobilität", gefördert durch die Behörde für Wissenschaft, Forschung, Gleichstellung und Bezirke (BWFGB) der Freien und Hansestadt Hamburg), durchgeführt.
... According to the data types, visual data mining technology can be classified into five categories: time-varying data and information visualization visualization mining, text data and information visualization mining, media data and information visualization visualization mining, network structure data and information visualization visualization mining, and multivariable data and information visualization visualization mining. The literature proposed an air transport database system based on cloud services (Niklaß et al. 2020). This system uses big data from various sources, uses databases to store these data sources, and uses open source tools to perform queries, searches, processes and visualizations. ...
Aerobics is a difficult gymnastics event, which requires very high skills for athletes. At present, the traditional video analysis method is mostly used in the simulation system of aerobics training management competition, which has some problems such as low analysis efficiency and complex data processing. Therefore, the purpose of this study is to design and implement an optical imaging detection method based on data information visualization, so as to provide an efficient and accurate aerobics training management competition simulation system. In this paper, an aerobics training management competition simulation system is designed by using optical imaging technology and data information visualization method. The system monitors and records athletes’ key movements in real time through camera equipment, and then transforms the monitored movement data into intuitive visual images by using data information visualization technology. The application effect of the developed optical imaging detection method based on data information visualization in the simulation system of aerobics training management competition is verified by experiments. The experimental results show that the system can effectively and accurately monitor the key movements of athletes, and display and analyze them through intuitive visual images.
... Figure 1 shows an exemplary scenario how such a network could look like and evolve over time for the city of Hamburg, Germany. These scenario simulations were performed in the work of Niklaß et al. [6]. proach guidance has been around for at least a decade [3]. ...
... Figure 1 shows an exemplary scenario how such a network could look like and evolve over time for the city of Hamburg, Germany. These scenario simulations were performed in the work of Niklaß et al. [6]. ...
... Thus, operational demand would match very well with the system's performance. [6]. The core service volume covered by the system is shaded in blue for each of the scenarios. ...
