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Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten. Estimating Advertisement Revenue for Robocabs
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Volltext urn:nbn:de:0011-n-5697211 (775 KByte PDF) MD5 Fingerprint: af5b44173d5b697c2e456e5d5ee26767 Erstellt am: 4.1.2020 |
| Transportation research procedia 41 (2019), S.511-524 ISSN: 2352-1465 |
| International Scientific Conference on Mobility and Transport (mobil.TUM) <2018, Munich> |
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| Englisch |
| Zeitschriftenaufsatz, Konferenzbeitrag, Elektronische Publikation |
| Fraunhofer IAO () |
Abstract
Connected, autonomous driving and social sustainability issues in urban environments demand to rethink the way, in which public and private transport is financed. The idea of in-vehicle advertisement is often discussed in press and literature as the prevailing solution for a cheap or even free-to-use mobility (see e.g. Gergshorn, 2017; Bertoncello et al., 2016). However, a transparent calculation of the revenue potentials and distributions is still missing. Within this paper, a data-driven approach is conducted. Based on real-world datasets about mobility demand and supply, a fleet of autonomous taxis – so-called Robocabs – is simulated and the advertisement revenue for multiple trips in New York City (NYC) is predicted. Within the analysis, we formulate three revenue model scenarios: One conservative and two, which focus especially on new advertisement opportunities for Robocabs. The conducted calculations show that advertisement approaches are not sufficient to guarantee a free-to-use Taxicab fleet: The average proportion of advertising revenue relative to the taxi fare varies from 1.99% in the first scenario to 5.56% in the third. Additionally, the dispersion of per-trip-revenue increases too, posing additional challenges with respect to the attribution of the value.