Although several (semi-) automatic parking systems have been presented throughout the years –, car manufacturers are still looking for low-cost sensors providing redundant information about the obstacles around the vehicle, as well as efficient methods of processing this information, in the hope of achieving a very high level of robustness. We therefore investigated how Local Motion Sensors (LMSs) , , comprising only of a few pixels giving 1-D optical flow (OF) measurements could be used to improve automatic parking maneuvers. For this purpose, we developed a low computational-cost method of detecting and tracking a parking spot in real time using 1-D OF measurements around the vehicle as well as the vehicle's longitudinal velocity and steering angle. The algorithm used was composed of 5 processing steps, which will be described here in detail. In this initial report, we will first present some results obtained in a highly simplified 2-D parking simulation performed using Matlab/Simulink software, before giving some preliminary experimental results obtained with the first step in the algorithm in the case of a vehicle equipped with two 6-pixel LMSs. The results of the closed-loop simulation show that up to a certain noise level, the simulated vehicle detected and tracked the parking-spot assessment in real time. The preliminary experimental results show that the average refresh frequency obtained with the LMSs was about 2-3 times higher than that obtained with standard ultrasonic sensors and cameras, and that these LMSs therefore constitute a promising alternative basis for designing new automatic parking systems.