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In the automotive area, mobile robot theory with artificial intelligence had demonstrated an incredible potential and interest of several researchers that are involved on the issue of board intelligent systems on passenger cars to perform daily jobs as, navigation without collision, control vehicle speed, parking, etc. This paper will present a path planner using a neural controller trained based on potential fields, in order to determine the trajectory and a fuzzy controller to determine the differential robot kinematics for the parallel parking maneuver task. A simulator presents the neural network training and the fuzzy logic application, from any initial point. The trajectory results can be compared with the theory and the vehicle kinematics can be verified through the simulator.

Each more the consumer uses the vehicle noise, vibration, and harshness (NVH) attributes to define the vehicle model when purchasing a car, so the sound quality development is very important to guarantee the automaker success in a competitive market. Several vehicle components contribute to the consumer sound quality perception, as engine, gearbox and exhaust systems. So those components improvement is necessary in order to enrich the sound perception. In this article will be developed a case study that evaluates the contribution and the characteristics of the irradiated noise from the power steering system, which was classified as moan, whine and hiss noise, defines objectively each phenomena and evaluate the proposed systems.