Public transportation mode like taxi service consider as an essential service in every city that can serve all gender, age, and level of people, used for to move at any time and everywhere inside or outside the city. with the new entrance of technology for transportation, the taxi industry is undergoing a rapid digital transition like many other fields, that include new inventory like Uber and Careem for taxi sharing used by smartphones. Most of the time, taxi vehicles' distribution is imbalanced due to passengers and taxi drivers' unorganized demand. The plan is always left to the driver to estimate the right place to drive in, making passengers waiting time is longer in some areas, and taxi drivers tour without giving exemplary service. That will lead to loss of income for taxi service providers and reduce the service's passenger satisfaction due to long waiting time without finding the service when needed. To solve this problem, the ability to forecast the proper place and time for taxi demand will help in solving this issue and increase income and customer satisfaction. Solving this issue will bring advantages for passengers, taxi drivers, and the service provider. Such service providers like Dubai RTA or Uber can reallocate taxi vehicles in advance to service a wider area of demand. Of course, we are not able to know where the passenger will be in a short time. However, through experience, we will know the approximate numbers of people in a particular area that require a certain number of taxis, and this is what we are looking for to reduce the waiting time. This issue is considered the right question for an approach for competitive study and using different algorithms. Can it provide the service provider with a good view of the number of riders waiting for the taxi vehicle? Moreover, a clear idea of locating the vehicles based on passengers waiting for the service. Passenger demands can also have too irregular patterns for people to understand but can be identified by a competitive study.
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Abu Taleb, Samer Kamal, "Dubai Taxi Demand Hotspots Prediction" (2020). Thesis. Rochester Institute of Technology. Accessed from