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.

In general, the road roughness is managed by the roughness factor(or level, index) which is numerically or quantitatively generated(or converted) from the surface profile. However, it should be mentioned that the various roughness indexes including IRI(i.e. International Roughness Index) consider only vertical displacement and one longitudinal profile. In this research, the new roughness index, which evaluates reasonably the ride quality, was developed through the extensive correlation analysis between various vehicle behavior and ride quality. The bounce and pitch of moving vehicle are caused by the change of longitudinal profile. On the other hand, the roll is caused by the difference of the left and right profiles. Since the pitch is caused by the bounce difference between the front and rear axles of a vehicle, the two values occur in a similar pattern. In this study, the bounce and roll of a vehicle were predicted with a half car model, which is connected with two quarter car models. A half-car model was used to calculate the roll rotation angle of the vehicle body according to the change of the road profile. The roll rotation angle was used to calculate the coordinates of the head position of the passenger in the passenger seat. Finally, the coordinates were used to calculate the horizontal and vertical displacement of the head position. The new roughness index is the cumulative RMS value of the horizontal and vertical displacement occurring at the head position while moving at a speed of 80 km/h per km. The first and second experiment results presented that the coefficient of determination(i.e. R2) for the new roughness index was the highest with 0.80. Moreover, the R2 values of MRI, HRI, and RN were also relatively high such as 0.73 ~ 0.79. The feasibility test was conducted on sections that show the greater IRI variation between left and right wheel-pass among the pilot sites. Because a prediction result came from MRI and IRI, the difference between KERI and MRI was relatively lager with the increment of IRI difference between right and left wheel-pass. In this case, the roll was high, and the satisfaction of the ride quality was relatively low. Based on the other field survey results obtained in Seoul, the portion of IRI difference between left and right wheel-pass was above 0.4m/km that presented approximately seven times higher value than the measured IRI values on the expressway. In addition, the sectors showed IRI difference level higher than 2.0m/km were approximately 70 times higher than those in expressway. Thus, it is possible that the KERI could successfully and reasonably evaluate the ride quality on various road types.