과적단속용 WIM 시스템의 이차적 검측영향인자 분석 (Analysis of Secondary Influencing Factors for the WIM System Used in Overload Enforcement)

서지정보

· 발행기관 : 한국도로학회
· 수록지 정보 : 한국도로학회논문집 / 25권 / 4호 / 25 ~ 35페이지
· 저자명 : 이동해, 이종석, 조재우, 김종우, 김태상

초록

PURPOSES : In this study, we aim to broaden the understanding of the factors influencing the accuracy of WIM systems for overload enforcement. Particularly, we explored the proportions and causes of secondary influencing factors (driving path, vehicle class, and acceleration), which have been relatively less studied and reduced the accuracy of the WIM system.
METHODS : Overload enforcement data were recorded by the WIM system, and enforcement officers were gathered. The ratios of each data point, which are the relative errors, are used to estimate the accuracy of the WIM system. These relative errors were classified into four driving-path groups, four vehicle-class groups, and three acceleration groups. The change in the accuracy of the WIM system caused by each influencing factor was analyzed by comparing the difference in the average relative error between the classified groups. Analysis of variance (ANOVA) and Welch's ANOVA were used to determine significant differences between groups.
RESULTS : Vehicles departing from a normal driving path make it difficult for the GVW compensation algorithm of the WIM system to operate properly. For these abnormal paths, the standard deviation of the average GVW relative error was 22%. There was no specific trend in the difference in accuracy by vehicle class. However, we found that the rear axle and retractable axle were the main causes of the reduced GVW accuracy in each vehicle class. The average GVW relative error remained the same regardless of the acceleration, but the average FAW relative error of the accelerated vehicle was approximately 2.5% lower than that of the unaccelerated vehicle.
CONCLUSIONS : An abnormal driving path, lifting of a retractable axle, and rapid acceleration (or deceleration) reduce the accuracy of WIM systems. Intelligent transportation systems, such as traffic signals, telematics devices, and applications that induce desirable driving are required for effective overload enforcement. Additionally, it is necessary to smoothen the road pavement to minimize the dynamic effects on the rear axle.

영어초록

PURPOSES : In this study, we aim to broaden the understanding of the factors influencing the accuracy of WIM systems for overload enforcement. Particularly, we explored the proportions and causes of secondary influencing factors (driving path, vehicle class, and acceleration), which have been relatively less studied and reduced the accuracy of the WIM system.
METHODS : Overload enforcement data were recorded by the WIM system, and enforcement officers were gathered. The ratios of each data point, which are the relative errors, are used to estimate the accuracy of the WIM system. These relative errors were classified into four driving-path groups, four vehicle-class groups, and three acceleration groups. The change in the accuracy of the WIM system caused by each influencing factor was analyzed by comparing the difference in the average relative error between the classified groups. Analysis of variance (ANOVA) and Welch's ANOVA were used to determine significant differences between groups.
RESULTS : Vehicles departing from a normal driving path make it difficult for the GVW compensation algorithm of the WIM system to operate properly. For these abnormal paths, the standard deviation of the average GVW relative error was 22%. There was no specific trend in the difference in accuracy by vehicle class. However, we found that the rear axle and retractable axle were the main causes of the reduced GVW accuracy in each vehicle class. The average GVW relative error remained the same regardless of the acceleration, but the average FAW relative error of the accelerated vehicle was approximately 2.5% lower than that of the unaccelerated vehicle.
CONCLUSIONS : An abnormal driving path, lifting of a retractable axle, and rapid acceleration (or deceleration) reduce the accuracy of WIM systems. Intelligent transportation systems, such as traffic signals, telematics devices, and applications that induce desirable driving are required for effective overload enforcement. Additionally, it is necessary to smoothen the road pavement to minimize the dynamic effects on the rear axle.

참고자료

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