The traffic sign recognition system is a support system that can be useful to give notification and warning to drivers. It may be effective for traffic conditions on the current road traffic system. A robust artificial intelligence based traffic sign recognition system can support the driver and significantly reduce driving risk and injury. It performs by recognizing and interpreting various tr...

Traffic signs are characterized by a wide variability in their visual appearance in real-world environments. For example, changes of illumination, varying weather conditions and partial occlusions impact the perception of road signs. In practice, a large number of different sign classes needs to be recognized with very high accuracy. Traffic signs have been designed to be easily readable for hu...

This study uses regression analysis to evaluate long-run traffic management system performance. Three important traffic management systems in the Twin Cities metro area—Ramp Metering, Variable Message Signs, and Freeway Service Patrols (the Highway Helper Program) were evaluated using multiple regression models to predict link speed and incident rate. We find that ramp meters increase freeway l...

A detection and recognition method of traffic signs is implemented based on traffic signs’ color and shape features. This method consists of image segmentation based on HSV color space, detection and affine transformation correction based on geometry features, extraction of eigenvector by using Gabor filter, Classification and recognition by Support Vector Machine (SVM). The above algorithms ar...

Traffic signs are designed to be clearly seen by drivers. However a little is known about the visual influence of the traffic sign environment on how it will be perceived. Computer estimation of the conspicuity from images using a camera mounted on a vehicle is thus of importance in order to be able to quickly make a diagnosis regarding conspicuity of traffic signs. Unfortunately, our knowledge...