Mining Metro Data to Determine Taxi Distribution in Peak Hours

  • Zainab Al Kashari The British University in Dubai, Dubai, United Arab Emirates
  • Fatma Al Taheri
Keywords: Data Mining, Taxi Distribution, Metro Ridership, Path Planning, Trip Planning, Transportation


Public transportation activities and processes can provide valuable data and information that be useful for public transportation management.  As a matter of fact, metro ridership data can be used to assess ridership and traffic flow, which can be useful for building interconnected public transportation system.  For instance, metro ridership can be used to understand intermodal relationship with taxi systems, further enabling taxi companies to capitalize on traffic flow and pressure that can be observed in metro ridership datasets.  Different data mining and data processing techniques can be of great use for determining taxi distribution based on metro ridership dataset. This study used data mining techniques to determine the traffic and transaction pressures on metro stations in Dubai, further identifying the peaks hours to direct the taxi drivers to the best destination.  Dataset was collected from Dubai Pulse, and preprocessed and manipulated.  Findings of this study indicated that high traffic pressures in Dubai Metro Red Line zone six, with peak points at three different times. Taxis can use traffic pressures at each station, and calculate arrival time to stations for optimal travel and revenue.


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