Speed is one of the major factors by which the traffic safety is affected. If the speed limit traffic signs on the road are recognised and displayed to a driver, this will be a motivation to keep the vehicle's speed within the permitted range. The purpose of this paper is to investigate Eigen-based traffic sign recognition which can aid in the development of Intelligent Speed Adaptation. This system is based on invoking the PCA technique to detect the unknown speed limit traffic sign and computes its best effective Eigen vectors. The traffic sign is then recognized and classified by using the shortest Euclidean distance to the different speed limit traffic sign classes. The system was trained using 24 037 images which were collected in different light conditions. To check the robustness of this system, it was tested against 1429 images and it was found that the accuracy of recognition was 97.5% which indicates clearly the high robustness targeted by this system.