Urban Air Mobility: Another Disruptive Technology or Just an Insignificant Addition?
Urban Air Mobility (UAM) describes flying vehicles that usually carry two to four passengers in urban areas. Vehicles are electric, may take off and land vertically, and – at least in the long run – are expected to fly autonomously to avoid carrying a pilot instead of passengers. Prototypes operate today, and companies such as, Airbus, Lilium and Uber Elevate proclaim that UAM will complement existing modes by flying vehicles with a range of 300 km at costs similar to a taxi, traveling across congested roads at a speed of 300 km/h. In this research project, the authors added UAM to an existing agent-based travel demand model called MITO (Microscopic Transportation Orchestrator). The model will be used to assess the potential to complement transit (or compete against it) in the Munich Metropolitan Area. While MITO is an operational model that was already implemented for this study area, two major enhancements were necessary to model UAM: 1. Mode choice: To model the usage of a new mode that is not in operation yet, two methods are commonly used. Either, stated preference surveys are conducted and used to estimate a mode choice model that includes the new mode, or an incremental logit model as proposed by Koppelman (1983) is used. In this project, both methods are combined. An incremental logit model selects a base mode (here: Auto Passenger) and specifically defines the changes in utility provided by the new mode (here: UAM). The existing nested mode choice model is extended by the mode UAM accordingly. To define the changes in utilities, a stated preference survey is used to better understand how fundamentally utilities may change for this rather futuristic mode. 2. Induced demand: Improvements to transport infrastructure and new modes that make travel faster, easier or cheaper commonly induce additional travel demand. This includes short-term changes in travel behavior and long-term changes in household relocation, car ownership and workplace location. In this project, mode choice logsums are used to model the increased trip generation after the introduction of UAM. Likewise, the destination choice model uses mode choice logsums to allow travelers to use destinations that are further away after the introduction of aerial mobility. Long-term adjustments are planned to be added in the future. Using the land use model SILO, mode choice logsums could also be used in household relocation and work location choice. The impacts on auto ownership are largely unknown, as many passengers might decide to drive their car to a UAM landing pod. The main benefit of modeling UAM is to quantify the potential impact. The agent-based design of the presented model also allows for equity analysis to better understand who benefits from the introduction of this new mode. At first look, the impact is likely to be small. Vehicles carry two to four passengers. If traffic operations were able to fly a vehicle from one location to another (such as from the airport to a downtown location) every five minutes, the system would carry on this origin-destination pair 24 to 48 passenger per hour. This number is far smaller than peak travel demand by auto or ground transit for any commercially used airport in an European metropolitan area. However, if UAM were to connect many origins and destinations in a metropolitan area, the impact could be much larger, particularly on highly congested origin-destination pairs with poor transit connections.
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- Abstract used by permission of Association for European Transport.
Association for European Transport (AET)1 Vernon Mews, Vernon Street, West Kensington
London W14 0RL,
- Pukhova, Alona
- Llorca, Carlos
- Moreno, Ana
- Zhang, Qin
- Moeckel, Rolf
- European Transport Conference 2019
- Location: Dublin , Ireland
- Date: 2019-10-9 to 2019-10-11
- Publication Date: 2019
- Media Type: Digital/other
- Pagination: 11p
- Monograph Title: European Transport Conference 2019
- TRT Terms: Air transportation; Infrastructure; Logits; Mobility; Mode choice; Origin and destination; Peak periods; Stated preferences; Surveys; Travel behavior; Travel demand; Urban transportation
- Subject Areas: Aviation; Operations and Traffic Management; Planning and Forecasting;
- Accession Number: 01751300
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 21 2020 12:52PM