| Language: | Slovenian |
|---|---|
| Year of publishing: | 2017 |
| Typology: | 2.09 - Master's Thesis |
| Organization: | UM FERI - Faculty of Electrical Engineering and Computer Science |
| Publisher: | A. Borko |
| UDC: | 004.032.26:004.383.4(043.2) |
| COBISS: |
20971286
|
| Views: | 866 |
| Downloads: | 110 |
| Average score: | 0 (0 votes) |
| Metadata: |
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| Secondary language: | English |
|---|---|
| Secondary title: | Using a neural network to control a simulated autonomous vehicle |
| Secondary abstract: | In the present research, we studied neural networks and their level of application in learning how to drive simulated autonomous vehicles. We created a 3D environment including a road on which the vehicles can train how to drive. Each vehicle has its own neural network that determines the direction and speed of the vehicle. We compared and studied different approaches to learning – evolutionary approach and supervised learning using the backpropagation method. The aim of this master thesis was to create a vehicle that is able to drive on the right side of the road and avoid the obstacles. |
| Secondary keywords: | neural network;evolutiuonary algorithms;3D simulation;autonomous vehicle; |
| URN: | URN:SI:UM: |
| Type (COBISS): | Master's thesis/paper |
| Thesis comment: | Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije |
| Pages: | IX, 65 str. |
| ID: | 10866641 |