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.

Recently, due to the rapid increase in vehicle accidents, research on improving seat belts and restraint system are being actively on going to solve the problems in vehicle for passengers. The characteristics of lap belt load and pelvic displacement were simulated through MADYMO program using Hybrid III 50th percentile male dummy to analyze the submarining by changing the collision speed and seat back angle by applying the forward collision pulse form accident scenario. As a result, the submarining occurred when the seat-back angle was 60° or higher at the collision speed of 50km/h or higher. Lastly, using the characteristics of the lap belt load and pelvic displacement when the anti-submarining belt (ANSB) system adapted, the pelvic displacement was reduced as well as submarining.

With increasing demands of transportation services for disabled or aged people, who need wheelchairs, it is recommended to install wheelchairs inside automotive vehicles. However, wheelchairs are not effectively safe devices during car crash unless they are properly fixed. So far, few data have been found related to wheelchair safety or characteristics during car crash, therefore, frontal crash simulations have been carried out based on the FE models of a dummy and a conventional wheelchair including the wheelchair fixing belts and the install plate in the present study. Head injury criteria (HIC) and motion criteria (MC) are investigated and the optimum value of the design variable was found by the Robust design.