PURPOSES : The purpose of this study is to propose the certification process of International Roughness Index measuring device, i.e., a method for evaluating riding quality on road surfaces. METHODS : ROMDAS was selected as a reference device for verifying the accuracy of the IRI measuring device and the reliability of ROMDAS was checked through leveling in the laboratory and outdoors. To verify four different IRI measuring devices in Korea, the proper field test section was selected and IRI evaluation was conducted. A distance measuring instrument (DMI) - for verifying the accuracy of mileage - and IRI (as an index of roughness) were selected as the main evaluation parameters. For DMI verification, five repeated experiments were conducted for a 1 km section and, for IRI verification, speed variables of 40 km/h, 60 km/h, and 80 km/h were selected. Each device was tested at each speed 10 times. The accuracy of the measurement device was analyzed by comparing the measurement results with the verification criteria. RESULTS : As a result of the comparative experiment between the leveling and ROMDAS devices, the deviation of each measurement point value was within 1 mm and the R2 value was 0.8, demonstrating an excellent correlation. As a result of DMI verification, the tolerance of the three devices was found to be within 0.1 %; however, one device had a tolerance of 0.8 %, indicating that correction was necessary. For IRI evaluation, the average IRI value of the two reference devices was 2.02 m/km and the Minnesota standard was used as an analysis criterion. After the test, only one of the four devices was found to be effective across all speed ranges. Therefore, it was determined that additional sensor calibration is required to improve accuracy. CONCLUSIONS : In this study, the IRI device accuracy was evaluated through field tests. Hence, a new certification process for the IRI test device was proposed via four steps. To improve the accuracy of the IRI measurement, it is necessary to periodically verify the device. If this proposed certification process is applied, the accuracy of the IRI devices can be improved.

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.

PURPOSES: This study aims to develop a rational procedure for estimating the pavement roughness index considering vehicle wandering. METHODS: The location analysis of the passing vehicle in the lane was performed by approximately 1.2 million vehicles for verification of the wandering distribution. According to verification result, the distribution follows the normal distribution pattern. The probability density function was estimated using each lane's wandering distribution model. Then the procedure for applying a weighted value into the lane profile was conducted using this function. RESULTS : The modified index, MRIw, with consideration towards applying the wandering weighted value application was computed then compared with MRI. It was found that the Coefficient of Variation for distribution of lateral roughness index in the lane was high in the case of a large difference between each index (i.e., MRIw and MRI) observed. CONCLUSIONS : This result confirms that the new procedure with consideration of the weight factor can successfully improve the lane representative characteristics of the roughness index.