An adaptable and scalable least cost network for air-taxis in urban areas Study area: Manhattan, New York

Hildemann M, Delgado C

Abstract

The first part of this work explainsthe legal flight restrictions and concepts for possible future flight areas. The goal is to derive the necessary information for the selecting restricted areas for possible flight routes with the least effect to the citizens. These restrictions are implemented with a Geographical Information System. Secondly, the optimization potential of the non-restricted flight areas is examined. The optimization consists of the development of an adaptable and scalable least-cost network in the aerial space of Manhattan. The cost is the distance between 3D-points with avoiding the restricted airspace and considering the minimal negative impact on the citizens. The scalability of the network´s capacity is considered for times of high demand. Also, on-demand transportation and temporal impedances are considered by using dynamic geofences. The idea of the implemented geoprocessing model builds on designed paths for helicopters. Combined with proposed concepts of space agencies for optimal management of urban aerial space, a parameter-driven and semi-automatic model is developed. The limiting factors of the airspace are adaptable to the laws and restrictions of the city management of other study areas. The maps shall support the decision makers of the city management and of the space agencies to manage the urban airspace in the future.