This paper proposes an efficient method to locate the automated guided vehicle (AGV) into the parking position using artificial visual landmark. For automated transshipment system in container terminals, the port AGV is used to transport containers autonomously and efficiently. To co-operate with the transfer crane, accurate guiding and positioning system is required. Using computer vision algorithms that detect and track the object from the video streams, we extract the exact position and relative distance with respect to the parking position. The artificial landmark is designed for effective detection based on corner feature and color information. After detection phase finds the position of the landmark in the captured image, tracking phase follows the trace of the landmark in the successive image sequences. Tracking phase consists of two stages, estimation and refinement steps. Optical flow vector around the detected point in the current image is calculated by pyramidal Lucas-Kanade feature tracker, and it is used to estimate the current position of the landmark. Then, the refinement step uses some features of the landmark as references to correct the estimated position of the object. Whole process is performed in HSI color space so that the system can be robust to illuminant variation. Experiments show reliable results of parking movement of the AGV. Our approach is simple, effective and robust.