With the mandatory implementation of ESC for trucks starting in 2023, domestic truck manufacturers in South Korea are advocating for a relaxation of the maximum safe slope angle to achieve cost savings. However, there is a lack of research on the dynamic safety of trucks based on ESC installation and the relaxation of the maximum safe slope angle. This study evaluates the relationship between static safety factor (SSF) and the maximum safe slope angle, analyzing the dynamic stability of trucks through simulation considering various experimental variables. The results quantitatively demonstrate the impact of relaxing the maximum safe slope angle on dynamic safety and provide recommendations for future safety regulations.
PURPOSES : This study aims to perform a quantitative analysis of Forward Collision Warning and crash frequency using heavy vehicle driving data collected in expressway driving environments, and to classify the driving environments where Forward Collision Warnings of heavy vehicles occur for accident-prone areas and analyze their occurrence characteristics. METHODS : A bivariate Gaussian mixture model based on inter-vehicle distance gap and speed-acceleration parameters is used to classify the environment in which Forward Collision Warning occurs for heavy vehicles driving on expressways. For this analysis, Probe Vehicle Data of 80 large trucks collected by C-ITS devices of Korea Expressway Corporation from May to June 2022. Combined with accident information from the past five years, a detailed analysis of the classified driving environments is conducted. RESULTS : The results of the clustering analysis categorizes Forward Collision Warning environments into three groups: Group I (highdensity, high-speed), Group II (high-density, low-speed), and Group III (low-density, high-speed). It reveals a positive correlation between Forward Collision Warning frequency and accident rates at these points, with Group I prevailing. Road characteristics at sites with different accident incidences showed that on-ramps and toll gates had high occurrences of both accidents and warnings. Furthermore, acceleration deviation at high-accident sites was significant across all groups, with variable speed deviations noted for each warning group. CONCLUSIONS : The Forward Collision Warning of heavy vehicles on expressways is classified into three types depending on the driving environment, and the results of these environmental classifications can be used as a basis for building a road environment that reduces the risk of crashes for heavy vehicles.
The trend of heaviness causes the increase in the number of overloaded vehicles on a bridge, which is a difficulty in the decision of design live load. However, there is no established system to control the overloaded vehicles. In this paper, a management system to control the total number of heavy vehicles on a bridge using BWIM. The traffic management system uses the control methods based on approaching time intervals.