Developing and deploying a taxi price comparison mobile app in the wild: Insights and challenges

Anastasios Noulas, Vsevolod Salnikov, Desislava Hristova, Cecilia Mascolo, Renaud Lambiotte

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Résumé

As modern transportation systems become more complex, there is need for mobile applications that allow travelers to navigate efficiently in cities. In taxi transport the recent proliferation of Uber has introduced new norms including a flexible pricing scheme where journey costs can change rapidly depending on passenger demand and driver supply. To make informed choices on the most appropriate provider for their journeys, travelers need access to knowledge about provider pricing in real time. To this end, we developed OpenStreetCab a mobile application that offers advice on taxi transport comparing provider prices. We describe its development and deployment in two cities, London and New York, and analyse thousands of user journey queries to compare the price patterns of Uber against major local taxi providers. We have observed large heterogeneity across the taxi transport markets in the two cities. This motivated us to perform a price validation and measurement experiment on the ground comparing Uber and Black Cabs in London. The experimental results reveal interesting insights: not only they confirm feedback on pricing and service quality received by professional driver users, but also they reveal the tradeoffs between prices and journey times between taxi providers. With respect to journey times in particular, we show how experienced taxi drivers, in the majority of the cases, are able to navigate faster to a destination compared to drivers who rely on modern navigation systems. We provide evidence that this advantage becomes stronger in the centre of a city where urban density is high.

langue originaleAnglais
titreProceedings - 2018 IEEE 5th International Conference on Data Science and Advanced Analytics, DSAA 2018
rédacteurs en chefFrancesco Bonchi, Foster Provost, Tina Eliassi-Rad, Wei Wang, Ciro Cattuto, Rayid Ghani
EditeurInstitute of Electrical and Electronics Engineers Inc.
Pages424-430
Nombre de pages7
ISBN (Electronique)9781538650905
Les DOIs
Etat de la publicationPublié - 31 janv. 2019
Evénement5th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2018 - Turin, Italie
Durée: 1 oct. 20184 oct. 2018

Série de publications

Nom2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)

Une conférence

Une conférence5th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2018
Pays/TerritoireItalie
La villeTurin
période1/10/184/10/18

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