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A Decision Support System for Taxi Drivers
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
School of Spatial Planning and Development, Aristotle University of Thessaloniki, 54 124 Thessaloniki, Greece.
School of Rural & Surveying Engineering, Aristotle University of Thessaloniki, 54 124 Thessaloniki, Greece.
Center for Research and Technology Hellas, Hellenic Institute of Transport, 57 001 Thermi, Thessaloniki, Greece, Thermi.
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Number of Authors: 52023 (English)In: AIIT 3rd International Conference on Transport Infrastructure and Systems,TIS ROMA 2022: Conference Proceedings, Elsevier BV , 2023, p. 123-130Conference paper, Published paper (Refereed)
Abstract [en]

The taxi sector is being revolutionized worldwide due to innovative companies, such as Uber, Lyft and more, that are trying to acquire a share of the market. In the same context, contemporary businesses in Greece have started to expand their activities. This present research is subsumed into the concept of innovation in the conventional taxi sector in Greece and attempts to implement pioneering ideas, to offer better services for taxi customers and profitable financial circumstances for taxi owners and drivers. The main data source regarding the taxi trips are the Hellenic Institute of Transport and Taxiway, the largest taxi fleet management company that operates in Thessaloniki. The given data consisted of 170 taxi trips originating from a taxi stand in the city center, 1981 routes which began from the area around the taxi stand and 1832 trips of taxis that passed through the examined area near the stand. These data, in accordance with a financial analysis of taxis' operational costs, have been processed to produce statistical results, such as the mean waiting time in each stand or possible spots for a taxi to pick up a customer. The research relies on these data, for the sake of building an application in which taxi drivers would be advised on their dilemma of choosing between waiting in taxi stands or hailing in the surrounding area to find a customer. With the utilization of such a website, drivers can compare the predicted benefit values for hailing or standing alternatives aiming to optimize the taxi downtime. The analysis concluded that the system can potentially increase the average expected profit per trip, even by 50% in a comparison to a different decision taken by the taxi driver.

Place, publisher, year, edition, pages
Elsevier BV , 2023. p. 123-130
Keywords [en]
Decision support systems, Statistical analysis, Taxi, Taxi demand
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-333342DOI: 10.1016/j.trpro.2023.02.153Scopus ID: 2-s2.0-85159124691OAI: oai:DiVA.org:kth-333342DiVA, id: diva2:1784988
Conference
3rd International Conference on Transport Infrastructure and Systems, TIS ROMA 2022, Rome, Italy, Sep 15 2022 - Sep 16 2022
Note

Part of ISBN 9781713870913

QC 20230801

Available from: 2023-08-01 Created: 2023-08-01 Last updated: 2023-09-06Bibliographically approved

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Kaltsidis, Alexandros

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