The theme of the paper is the research and development of an algorithm for planning the path of an autonomous vehicle. The most important solutions so far are presented, and a development environment is defined in which the algorithm is made. For the development of the algorithm Udacity's simulator is chosen as it simulates the conditions on a fast three-track road. The algorithm and simulator communicate with the two-way communication; the simulator handles the sensor data to an algorithm that in return returns only the coordinates that the vehicle will pass in its trajectory. The algorithm loads the given data, and then transforms it into a Frenets coordinate system for easier and more precise calculation. Frenets coordinates calculate the parameters of the ego vehicle and the possible manners that can be taken on the road. Then, the paths for each of the states are defined and evaluated with respect to certain criteria and multiplied with respective weights. After defining the final path of the vehicle, it must be transformed back into the Cartesian coordinate system so that the simulator can handle the data. By evaluating the solution, it was concluded that the algorithm works as intended by the simulator, but this is not satisfactory for realistic road conditions that are unpredictable. The simulator is not a realistic view of road conditions since it only simulates a fast road with other vehicles, with no traffic signs or changes in constraints what makes the tests themselves unrealistic algorithm performance. The algorithm implementation on the Alpha board failed despite numerous attempts to enable communication between the simulator located on computer and the Alpha board via Ethernet.