Evaluation of business travel as a potential customer field of a local AAM market

Several studies examine Advanced Air Mobility (AAM) demand focusing on commuting and airport shuttle trips at this moment. Little activities are concentrating on business travel in general nor for AAM demand in special. Business travel as a generic term for any corporate purposed transport consists of four categories: Meetings, Incentives, Conventions and Exhibitions (MICE). Every business traffic comes along with its own character which has to be considered when modelling. After the transport generation based on their travel purpose and location, a discrete choice model evaluates different modes of transport to determine the market share for AAM. As business travel is expected to have a greater value of time, the modal share of AAM is anticipated be higher compared to more cost-sensitive use cases such as commuting. On the other hand, however, the market size of the overall business traffic could weaken this group of potential AAM passengers. In the field of this poorly investigated demand share, this approach presents a possibility of modeling local business traffic. Furthermore, this study assumes an adopted AAM mode of transport for this passenger group, which helps to understand the characteristics of future AAM demand

Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics.

Combining single-cell measurements of ERK activity dynamics with perturbations provides insights into the MAPK network topology. We built circuits consisting of an optogenetic actuator to activate MAPK signaling and an ERK biosensor to measure single-cell ERK dynamics. This allowed us to conduct RNAi screens to investigate the role of 50 MAPK proteins in ERK dynamics. We found that the MAPK network is robust against most node perturbations. We observed that the ERK-RAF and the ERK-RSK2-SOS negative feedback operate simultaneously to regulate ERK dynamics. Bypassing the RSK2-mediated feedback, either by direct optogenetic activation of RAS, or by RSK2 perturbation, sensitized ERK dynamics to further perturbations. Similarly, targeting this feedback in a human ErbB2-dependent oncogenic signaling model increased the efficiency of a MEK inhibitor. The RSK2-mediated feedback is thus important for the ability of the MAPK network to produce consistent ERK outputs, and its perturbation can enhance the efficiency of MAPK inhibitors

Estimating the Economic Viability of Advanced Air Mobility Use Cases: Towards the Slope of Enlightenment

While different vehicle configurations enter the AAM market, airlines declare different ticket fares for their operations. This research investigates the operating cost of an airline and the economic viability with the announced fare per km rates. For this purpose, three use cases in the metropolitan area of Hamburg showcase representative applications of an AAM system, whereby a flight trajectory model calculates a flight time in each case. The direct operating cost are investigated for each use case individually and are sub-classified in five categories: fee, crew, maintenance, fuel and capital costs. Here, each use case has its own cost characteristics, in which different cost elements dominate. Additionally, a sensitivity analysis shows the effect of a variation of the flight cycles and load factor, that influences the costs as well as the airline business itself. Based on the occurring cost, a profit margin per available seat kilometer lead to a necessary fare per km, that an airline has to charge

Can Urban Air Mobility become reality? Opportunities, challenges and selected research results

Urban Air Mobility (UAM) is a new air transportation system for passengers and cargo in urban environments, enabled by new technologies and integrated into multimodal transportation systems. The vision of UAM comprises the mass use in urban and suburban environments, complementing existing transportation systems and contributing to the decarbonization of the transport sector. Initial attempts to create a market for urban air transportation in the last century failed due to lack of profitability and community acceptance. Technological advances in numerous fields over the past few decades have led to a renewed interest in urban air transportation. UAM is expected to benefit users and to also have a positive impact on the economy by creating new markets and employment opportunities for manufacturing and operation of UAM vehicles and the construction of related ground infrastructure. However, there are also concerns about noise, safety and security, privacy and environmental impacts. Therefore, the UAM system needs to be designed carefully to become safe, affordable, accessible, environmentally friendly, economically viable and thus sustainable. This paper provides an overview of selected key research topics related to UAM and how the German Aerospace Center (DLR) contributed to this research in the project "HorizonUAM - Urban Air Mobility Research at the German Aerospace Center (DLR)". Selected research results that support the realization of the UAM vision are briefly presented.Comment: 20 pages, 7 figures, project HorizonUA

A Collaborative Systems of Systems Simulation of Urban Air Mobility: Architecture Process and Demonstration of Capabilities

Urban Air Mobility (UAM) presents a complex challenge in aviation due to the high degree of innovation required across multiple domains to realize it. From the use of advanced aircraft powered by new technologies, the management of the urban air space to enable high density operations, to the operation of specialized vertidromes serving as a start and end point of the vehicles, the UAM paradigm necessitates a significant departure from aviation as we know it today. In order to understand and assess the many facets of this new paradigm, a Collaborative Agent-Based Simulation is developed to holistically evaluate the system through the modelling of the stakeholders. In this regard, models of vertidrome air-side operations, urban air space management, passenger demand estimation and mode choice, vehicle operator cost and revenues, vehicle maintenance, vehicle allocation, fleet management based on vehicle design performance and mission planning are brought together into a single Collaborative System of Systems Agent-Based Simulation of Urban Air Mobility. Through collaboration, higher fidelity models of each domain can be brought together into a single environment which can then be exploited by all partners, achieving comprehensiveness and fidelity levels not achievable by a single partner. Furthermore, the integration enables the capture of cross-domain effects with ease and allows the domain-specific studies to be evaluated at a holistic level. Agent-Based Simulations were chosen for this collaborative effort as it presents a suitable platform for the modelling of the stakeholders and interactions in accordance with the envisioned concept of operations. This work presents the capabilities of the developed Collaborative System of Systems Agent-based Simulation, the development process and finally a visual demonstration. The objectives of this presentation are: • Detail the development process of the Collaborative System of Systems Agent-Based Simulation • Demonstrate a holistic simulation of UAM built through collaboration of multiple tools/modules such as vertiport and trajectorie

Automated Cargo Delivery in Low Altitudes: Business Cases and Operating Models

The project Automated Low Altitude Air Delivery (ALAADy) focuses on a transportation drone supposed to transport one metric ton of goods over a distance of 600 km with a cruise speed of 200 km/h. The aircraft is planned to operate under a newly established category of certification (EASA’s Specific category) that is intended to make certification less constraining and operations more affordable and equally safe compared to other means of air transportation. The present chapter introduces two possible applications of this aircraft, namely a commercial flight network for the delivery of agricultural spare parts in Europe, and a catastrophe relief mission for overflooded areas. In order to illustrate the parameters of the respective operations, both concepts are assessed using cost models as well as flight schedules and mission trajectories, respectively. This chapter’s purpose is to give impressions on the operational environments, particularly regarding economics and business-case establishment, that longer-range transportation drones have to comply with

Approach of Modeling Passengers' Commuting Behavior for UAM Traffic in Hamburg, Germany

Within the business model for urban air mobility (UAM), the passenger demand is a necessary input to build economic sustainable systems. This work aims to specify the UAM commuter demand in competition to other modes of transport by the example of the city of Hamburg in Germany. Based on pre-defined traffic cells by the city of Hamburg, a door-to-door traffic for commuter will be generated and distributed. Therefore, a discrete choice model will be used to predict the modal choice of passengers in the transport system. The resulting modal split in combination with the total market volume for commuter yields to the market share for commuting UAM traffic in Hamburg. Expecting a set of several itineraries in the city, a first statement about the catchment area indicates initial characteristics of a given vertiport network. By combining the market share for UAM in competition with the private car and a public transport system as well as the total market volume for commuting traffic, the passengers’ interest for each route of the itinerary set will be evaluated. The model allows a tracking of single passenger routes due to an investigation starting at an origin traffic cell and ending in a destination one. In comparison to a top-down approach, our model provides the opportunity to assess catchment areas for vertiports, find characteristics of the traveler and generate high and low demand itineraries

Optimized capacity allocation in a UAM vertiport network utilizing efficient ride matching

In this study, we present an approach that allows to design efficient UAM fleets and corresponding vertiport networks for specific demand patterns. Therefore, we apply a trajectory-based simulation model that controls the circulation of vehicles in a UAM network. The model allocates vehicles from an unlimited fleet pool to the requested missions, such that the boundary conditions of the optimization are fulfilled. Applying a combination of graph-based optimization and solving integer linear programming problems, a ride matching algorithm is implemented that minimizes empty relocation flights in the network and reduces the fleet size. The results comprise the quantification of a fleet pool, defined by fleet size, fleet mix, and starting positions in the vertiport network. We analyze a set of 20 vertiports in the City of Hamburg, Germany, regarding the local peak loads of parking positions that are needed for battery charging and waiting periods of unoccupied vehicles. The results show that the reduction of battery charging time has a significant impact on fleet size, which affects the minimum ground infrastructure requirements as well. Finally, the fleet analysis shows that average load factors of 45% are feasible at fleet sizes with varying occupancy rates of up to 80%