Virtual Reality Application on Road Markings’ Visibility Analysis

Abstract

The most important function of road markings is to guide road users; therefore, their visibility, in relation to retroreflectivity (R_L), plays an essential role in the markings’ performance at nighttime. Researchers have applied field experiments to determine the minimum acceptable levels of markings’ R_L. However, field studies usually involve a large investment of time, personnel, space, and budget. This paper presents a preliminary study that adopted virtual reality (VR) techniques to establish an immersive driving environment for the R_L analysis of yellow markings. The objective is to evaluate the minimum required marking visibility for road users, especially senior drivers, while driving at nighttime. The brightness feature created in the VR model does not simulate the optical behavior of markings’ glass beads, but it simulates the marking’s visibility in relation to detection distance at each test drive. This is an alternative method to correlate the field R_L and the VR simulation model through the equivalent detection distances that were recorded by the observers who participated in both field and VR driving tests. The relationship between the field markings’ R_L, 80 to 130 mcd/m²/lx, and simulated markings’ brightness was successfully established with its limitations of R_L between 80 and 130 mcd/m²/lx. Three age clusters are involved in this study, namely 20–30, 40–50, and 60+ years old, with 30 people in each cluster. The simulation study found that the driver’s behavior in relation to reaction time is highly related to age cluster but not driving speed or R_L. The average reaction times for the three age clusters are 0.438 s, 0.499 s, and 0.522 s, respectively. However, the perception reaction time 2.5 s was considered while calculating the required R_L for markings. Results found that the minimum required yellow markings’ R_L increases with driving speed, and it requires 80 mcd/m²/lx for 50 km/h and 130 mcd/m²/lx for 65 km/h to satisfy the 85 percentiles of the driving population in Taiwan.