This study aims to validate the feasibility of using LiDAR reflectivity data to quantitatively estimate the retroreflectivity of road lane markings. The goal is to establish the optimal scanning conditions considering the channel position, angle of incidence, and vehicle speed for an accurate and consistent retroreflectivity assessment in mobile environments. Fifteen standard lane marking samples with known retroreflectivity values were scanned using an OS1-128 LiDAR sensor under controlled field conditions. A two-phase experiment was conducted: (1) a speed-based test to assess the influence of vehicle velocity (20-80 km/h) on LiDAR reflectivity measurements, and (2) a channel–angle–distance test using a static testbed to analyze the relationship between retroreflectivity, LiDAR channel position (that is, the angle of incidence), and measurement distance. Ground truth retroreflectivity values were obtained using a high-precision handheld retroreflectometer. Reflectivity measurements showed a strong correlation with standard retroreflectivity values, particularly at scanning angle between 100-115° and distances of 4.9-5.6 m. The coefficient of determination (R2) exceeded 0.97 across optimal conditions. Speedrelated tests confirmed that the LiDAR-based reflectivity remained stable with a minimal RMSE (< 5), even under high-speed driving scenarios. LiDAR sensors provided reliable and contactless estimates of pavement marking retroreflectivity when the channel angle and scanning distance were appropriately selected. The findings demonstrated that channel-specific calibration and incidence angle correction significantly improved the measurement accuracy. This suggests a practical path forward for automated large-scale retroreflectivity monitoring in road asset management systems.
This project aimed to understand the near-infrared (NIR), intensity, and reflectivity characteristics of LiDAR for measuring retroreflectivity and to understand the correlation between the characteristics of LiDAR and retroreflectivity. A 600 m-testbed was investigated using a survey vehicle equipped with LiDAR, and the testbed retroreflectivity and LiDAR data measurement values were compared. The reflectivity and intensity at night were not affected by sunlight compared with daytime, enabling stable data collection. However, NIR reacted very sensitively to sunlight, and the difference between daytime and nighttime NIR values was very large. In addition, by comparing the absolute error between the retroreflectivity and LiDAR data, we observed that the reflectivity was consistent with the data difference between day and night, and it was not significantly affected by sunlight. However, the intensity showed that the daytime measurement data were more scattered than the nighttime measurement data, resulting in low-precision collection stability caused by sunlight. An analysis of the correlation between retroreflectivity and LiDAR data using 40 data points revealed that the reflectivity and intensity data at night were highly correlated with retroreflectivity, with a P-value of less than 0.05. Reflectivity and intensity values at night correlate with retroreflectivity. The NIR light is sensitive to sunlight. Thus, it can be used as a solar correction index for future retroreflectivity analyses using intensity.
PURPOSES : It is well known that experts determined the current standard dimensions of freeway lane markings. However, rigorous engineering rationale could be insufficient regarding whether or not the standard dimensions account for how visible the markings are to the driver. In this study, we seek to optimize the dimensions of freeway lane markings to improve their visibility to drivers.
METHODS: The study was conducted as follows. First, alternative lane marking dimensions were selected which could be installed in a test construction site. Second, a video recording was made while driving on the test construction site. Third, subjects were shown the recorded video and then instructed to indicate their preference from among the various lane markings. Lastly, t-tests were applied to assess the statistical significance of differences in the preferences expressed.
RESULTS : According to the t-test results, there was no significant difference in the preferences expressed regarding the lane marking widths. However, with regard to the dimensions of freeway lane marking, which represents line marking lengths, gap lengths, and widths of marking, the subjects expressed a preference for specific dimensions such as 6 m:12 m,13 cm, 8 m:12 m,10 cm and 6 m:12 m,10 cm.
CONCLUSIONS : In considering the dimensions of freeway lane markings and their relation to visibility by the driver, it was found that dimensions such as 6 m:12 m,13 cm, 8 m:12 m,10 cm and 6 m:12 m,10 cm.
본 연구에서는 하이패스 차로의 속도감소를 유도하기 위한 적절한 노면표시를 도출하기 위하여 감성공학적 분석방법을 활용하여 연구를 수행하였다. 현재 고속도로 영업소에서는 감속유도를 위하여 하이패스 차로에 갈매기 노면표시를 설치하여 운영하고 있다. 본 연구에서는 하이패스 차로의 감속유도를 위하여 갈매기 노면표시 및 Peripheral Transverse Bar(PT bar)에 대한 효과평가를 실시하고, 두 가지 노면표시를 조합하여 6가지 시나리오를 도출하였다. 도출된 시나리오에 대하여 이용자의 Perception 측정 및 분석을 통한 노면표시 설계 시 Human Factor를 반영할 수 있는 방법론을 제시하였다. 분석결과 빗살무늬의 PT bar 및 60˚ 각도의 갈매기 노면표시의 조합시나리오가 가장 적절한 노면표시로 선정되었다. 본 연구의 결과는 하이패스 차량들의 통과속도를 감소시켜 고속도로의 안전성을 높일 수 있을 것으로 기대된다.