Dynamic monitoring of taxi demand profiles, utilizing location-specific information in large metropolitan areas
| Autor: | Dimitriou, Loukas, Christodoulou, C., Kourti, E., Christodoulou, Symeon E. |
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| Přispěvatelé: | Christodoulou, Symeon E. [0000-0002-9859-0381], Dimitriou, Loukas [0000-0002-8427-058X] |
| Rok vydání: | 2016 |
| Předmět: |
Decision support system
Occupancy International trade Metropolitan areas 01 natural sciences Transport engineering Global Positioning System 0502 economics and business 0103 physical sciences Demand 010306 general physics Policies Electronics and Communications Abstracts (EA) 050210 logistics & transportation business.industry Wireless network Specific-information 05 social sciences Quality Metropolitan area Variety (cybernetics) Real time Electronics and Communications Milieux (General) (EA) [90] Public transport Electronics business |
| Zdroj: | Proceedings of the 18th Mediterranean Electrotechnical Conference: Intelligent and Efficient Technologies and Services for the Citizen, MELECON 2016 The Institute of Electrical and Electronics Engineers, Inc.(IEEE) Conference Proceedings. |
| DOI: | 10.1109/melcon.2016.7495409 |
| Popis: | Urban mobility, especially in Metropolitan Areas has drawn the attention of scientists for many decades. As increasing volumes of urban data are captured and become available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based decision support systems and policies. Sensing and wireless networking technologies are increasingly deployed in transportation systems due to the fact that they provide updated and reliable information. In this study, Taxi demand profiles are monitored from data that offer the real-time occupancy status and Global Positioning System (GPS) location for three taxi fleets, during the New Year's day. This dataset provides rich spatiotemporal information about customers demand and their mobility patterns. However, analyzing these data presents many challenges. The data are complex, containing geographical and temporal components in addition to multiple variables associated with each trip. Despite all these, real-time information gives us the opportunity to export variety of 'heatmaps', providing evidence relating to the mobility of the day. Furthermore, the conclusions of this study should help improve coordination of taxi services quality and increasing taxi fleet utilization. 1 6 |
| Databáze: | OpenAIRE |
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