Neural Network and IoT-based Test Maneuver Deployment for 2 DoF Vehicle Simulator

Abstract

This paper presents the driving scenarios deployment for 2 DoF (Degree of Freedom) vehicle simulator based on IoT (Internet of Things) and Neural Network. The controller structure is chosen as Neural Network-based controller is preferred as the transferring appropriate accelerations in 3 axes in the 2 DoF manipulator evokes a nonlinear problem. Due to the microcontroller used in the vehicle simulator to perform Neural Network calculations has limited processing capacity and speed, IoT-based computing and data transferring are chosen. Firstly, an open-loop measurement is performed to identify the vehicle simulator and to generate the training data for the neural network. Thereafter the acceleration data on the axes and the control signals are logged. Secondly, the neural network training is carried out with the logged data. Finally, the trained neural network was tested with various driving maneuvers. And the measurements are evaluated.