PURPOSES : In this study, the effects of installation of diagonal crosswalks on traffic flow depending on the types of intersections are analyzed. METHODS : Scrambled crosswalks have advantages in the traffic safety. Therefore, a comparative analysis of the overall average delay before and after installation of the scrambled crosswalk was conducted using VISSIM. RESULTS: The overall average delay for the scrambled crosswalk decreased when the traffic volume ratio of the major to the minor street is 1: 6 in 2-by-1 and 3-by-1 types of intersections. The scrambled crosswalk improved efficiency of traffic operation in intersections: higher traffic volume for a major street, lower traffic volume for a minor street, and longer cross-distance for a major street. CONCLUSIONS: This study can be used to determine when a scrambled crosswalk should be installed to improve operational efficiency.

With the increasing role of environmental design in promoting urban safety, new design attempts have been made to improve pedestrian safety in crosswalks. This study proposes an evidence-based design solution for improving crosswalk function by conducting simulations and field experiments. Drivers with more than one-year driving experience participated in this study. Four different crosswalk design patterns were prepared: (1) a zebra pattern, (2) zebra pattern with colored triangles, (3) 3D pattern, and (4) art pattern with unique colors and design. The results supported that the zebra pattern with colored triangles could be the most effective solution for crosswalk design by increasing visibility, attention, deceleration, and landscape aesthetics. This study provided objective data to support the performance of various crosswalk patterns and suggested the need to reevaluate the present crosswalk design guidelines.

Crosswalk detection is an important part of the Pedestrian Protection System in autonomous vehicles. Different methods of crosswalk detection have been introduced so far using crosswalk edge features, the distance between crosswalk blocks, laser scanning, Hough Transformation, and Fourier Transformation. However, most of these methods failed to detect crosswalks accurately, when they are damaged, faded away or partly occluded. Furthermore, these methods face difficulties when applying on real road environment where there are lot of vehicles. In this paper, we solve this problem by first using a region based binarization technique and x–axis histogram to detect the candidate crosswalk areas. Then, we apply Support Vector Machine (SVM) based classification method to decide whether the candidate areas contain a crosswalk or not. Experiment results prove that our method can detect crosswalks in different environment conditions with higher recognition rate even they are faded away or partly occluded.