Demand Estimation for Aerial Vehicles in Urban Settings

Abstract

The idea of flying has always fascinated mankind. A century ago it became reality when in 1914 the first commercial flight was offered. In recent times, many entities are planning, developing and testing aerial vehicles and systems that will move goods and people in urban scenarios. Consequently, the need to develop appropriate planning tools and to investigate the potentials for this kind of transportation is needed. In this paper we present a methodology for simulation and demand estimation for personal aerial vehicles (PAVs) in urban settings. The methodology is then utilized to analyze the impacts of PAVs with different vehicle and system parameters on the demand. The findings show that with higher automation and falling prices, PAVs have a potential to be an important transportation mode, by serving not only mid-distance trips, but also shorter trips in urban settings. The analysis also show that unlike for car and public transport service, vehicle parameters of PAVs have a substantial impact on the demand and turnover. Furthermore, an optimization procedure that minimizes fixed costs of the PAVs by minimizing the fleet size and variable costs by minimizing the empty kilometers of PAVs for the estimated demand in the region of Zurich, Switzerland, is proposed. Optimized service ensures that much wider range of possible vehicle concepts can be utilized to serve the demand.

The Prospects of on-demand Urban Air Mobility in Zurich, Switzerland

“…As the Zurich airport is well connected by public transport services and taxi fares are otherwise cheaper than UAM this is expected. Comparing the results to earlier work on estimating potential demand for UAM in Zurich [11], it is noticeable that the estimated demand is drastically lower when process times, access/egress trips, and infrastructure placement are included in the decision process. While the present work does not cover all possible combinations of speed, cost, and process time it still presents some important results: faster VTOL vehicles might not be able to compensate for additional process time, even though they can attract more users.…”

“…They find that travel time, travel cost, and safety may be critical determinants for the adoption of UAM. [11] shows how the demand for a UAM service might look like in Zurich, Switzerland, by allowing for pick-up and drop-off to take place anywhere in the study area. The study shows that vehicle speed and access time have substantial impact on demand.…”

Artificial Intelligence, Transport and the Smart City: Definitions and Dimensions of a New Mobility Era

“…Automation will allow PAVs to carry passengers with no piloting skills, making them much more accessible to anyone in practical terms. Infrastructure requirements, such as the number of landing and parking spaces, proper flying corridors, interaction with other modes and synergies with autonomous ground vehicles (PAVs and CAVs can benefit and complement each other), may allow PAVs to contribute significantly in the decrease of congestion and pollution if planned and implemented in a right way [49]. Nonetheless, despite innovation progress in the PAV concept development and related technologies, there are still key challenges that remain regarding public acceptance, traffic safety, expensive infrastructure, disaster management, trespassing and unnecessary surveillance, visual intrusion and excessive air traffic concerns [47,50].…”

Long-term application potential of urban air mobility complementing public transport: an upper Bavaria example

“…As previously mentioned, the results of an initial travel demand generation via MITO was fed into the agent-based transport simulation MATSim which has been extended to enable the simultaneous simulation of ground-and aerial-based transportation modes [11][12][13]. Additionally to ground-based transportation (e.g.…”