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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 54668 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Gholampour, Iman
- Abstract:
- In the transportation industry, one of the most important and fundamental problems is the traffic of vehicles in the transportation roads. This problem is especially seen in large and densely populated cities such as Tehran. If traffic control is not done properly, it can lead to problems such as reduced traffic dynamics, environmental pollution, wasted drivers' time, disorder and loss of energy. If the traffic control is done after creating a traffic problem, it will not bring good results and will have low efficiency. For this reason, optimal traffic management and control has been raised as an important issue, especially in large cities. Predicting traffic flow is one of the important and basic parameters in the discussion of traffic control and management and proper operation of intelligent transportation system, therefore it is necessary to predict the traffic model and traffic flow with low error and high accuracy. In this research, Gaussian processes method has been used for traffic forecasting and modeling. for this purpose, traffic data in Tehran has been used. The distinguishing feature of this method compared to other methods is the possibility of using prior knowledge and controlling the general behavior of the model using kernel functions and hyperparameters. Using this method, effective traffic points are identified by the model itself
- Keywords:
- Gaussian process ; Traffic Modeling ; Traffic Data ; Automatic Feature Selection ; Computationally Efficient Gaussian Processes ; Gaussian Process Estimation Methods
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