Since the road management paradigm has changed into the user-oriented circumstance, the functionality of the crucial road maintenance factors became important than before. Among these factors, the roughness directly related to the ride quality for driver became to get more attention. IRI(International Roughness Index) is recently the most widely used roughness indices in the world. IRI is a reasonable index that reflects the vertical displacement(bounce) of vehicle as the road profile changes. Since IRI reflects the vertical behavior of vehicle, it reflects ride quality indirectly. However, there are various rotational behaviors such as roll, yaw, and pitch in addition to the vertical displacement. Profiles, which MRI range was 1.13-4.12m/km, were measured in five sections and the profiles were entered into CarSIM to simulate vehicle behavior. As a result, the pitch was the largest in all sections, followed by roll and yaw, relatively. Especially, the amount of yaw is about 5% of the pitch or about 7% of the roll. The behavior of moving vehicle was measured using INS(inertial navigation system) and accelerometer in the section where the road surface profile was measured. As a result, as in the simulation, the pitch was the largest in all the sections and the amount of yaw is only about 7% of the pitch or about 18% of the roll. Field experiments were conducted to analyze the effect of the rotational behavior of the actual driving vehicle on the ride quality. 33 panels evaluated the ride quality on a ten-point scale while driving on 35 sections with various roughnesses. 35 test sections were selected considering the roughness distribution of actual expressway. The panel was selected considering age, driving experience, gender, and expertise. Of the total 1,155 responses, 964 responses were used for the analysis, except 191 responses measured at low driving speeds. In addition, the amount of vehicle behavior and road surface profile were measured using INS and laser. As a result of correlation analysis between MPR(mean panel rating) and vehicle behavior, correlation coefficient of bounce was the highest with 0.814, and the order of pitch was 0.798, and roll was 0.734, relatively. As a result of regression analysis for predicting ride quality, regression model combining bounce and roll was statistically the most suitable. This model is expected to reflect the ride quality more effectively because it can consider the vehicle behavior due to the longitudinal profile change of the road surface as well as the vehicle behavior due to the difference between the left and right wheel path road profile.

PURPOSES: The purpose of this research is to analyze the characteristics of panels that affect the evaluating results of riding quality and to evaluate the appropriateness of roughness management criteria based on ride comfort satisfaction. METHODS: In order to analyze the influence of panel characteristics of riding quality, 33 panels, consisting of civilians and experts, were selected. Also, considering the roughness distribution of the expressway, 35 sections with MRI ranging from 1.17 m/km to 4.65 m/km were selected. Each panel boarded a passenger car and evaluated the riding quality with grades from 0 to 10, and assessed whether it was satisfied or not. After removing outlier results using a box plot technique, 964 results were analyzed. An ANOVA was conducted to evaluate the effects of panel expertise, age, driving experience, vehicle ownership, and gender on the evaluation results. In addition, by using the receiver operating characteristics (ROC) curve, the MRI value, which can most accurately evaluate the satisfaction with riding quality, was derived. Then, the compatibility of MRI was evaluated using AUC as a criterion to assess whether the riding quality was satisfactory. RESULTS: Only the age of the panel participants were found to have an effect on the riding quality satisfaction. It was found that satisfaction with riding quality and MRI are strongly correlated. The satisfaction rate of roughness management criteria on new (MRI 1.6 m/km) and maintenance (MRI 3.0 m/km) expressways were 95% and 53%, respectively. As a result of evaluating the roughness management criteria by using the ROC curve, it was found that the accuracy of satisfaction was the highest at MRI 3.1-3.2 m/km. In addition, the AUC of the MRI was about 0.8, indicating that the MRI was an appropriate index for evaluating the riding quality satisfaction. CONCLUSIONS: Based on the results, the distribution of the panels’age should be considered when panel rating is conducted. From the results of the ROC curve, MRI of 3.0 m/km, which is a criterion of roughness management on maintenance expressways, is considered as appropriate.

PURPOSES: This study aims to evaluate the effects of vehicle dynamic behaviors on ride quality. METHODS: Simulation and field test were conducted to analyze the behavior of a driving vehicle. The simulation program CarSIM was applied and an INS (Inertial Navigation System) was used for field experiments. A small simulator was developed to simulate vehicle behavior such as roll, pitch, and bounce. The panels evaluated the ride quality in five stages from “very satisfied”to “very dissatisfied.”Experiments were conducted on a total of 144 cases of vehicle behavior combinations. RESULTS: In both simulation and field tests, pitch is the largest and yaw the smallest. Especially in the field test, the amount of yaw is very low, about 7% of pitch and 18% of roll. The sensitive and extensive analysis conducted related ride quality with changing the frequency and amplitude. It was found that the most sensitive frequency range is 8 Hz across all amplitudes. Moreover, the combination of the roll and bounce was most sensitive to the ride quality at the low-frequency range. CONCLUSIONS: This result show that the vertical vehicle behavior (bounce) as well as the rotational behavior (roll and pitch) are highly correlated with ride quality. Therefore, it is expected that a more reasonable roughness index can be developed through a combination of vertical and rotational vehicle behavior.

In this paper, the damping force of MRF(Magneto-Rheological Fluid) damper using Bingham-plastic model is studied and the performance of quarter car model using this damper is numerically analyzed. As a control algorithm, the sky-hook control is used for its convenience and effectiveness. The transmissibility of sprung mass and unspung mass is compared to that with the conventional passive damper and the feasibility of MRF damper is evaluated. And the design concept of fail-safe MRF damper is suggested to provide the damping force of conventional passive damper level in the case of controller malfunction. The control current and damping force is analyzed passing over the harmonic bumper.