TY - JOUR
T1 - Analysis of Regional Characteristics Affecting Vehicle Inspection Failure Rates Considering Spatial Autocorrelation
AU - Kim, Woosuk
AU - Kim, Do Gyeong
AU - Park, Jungsoo
N1 - Publisher Copyright:
Copyright © 2022 KSAE.
PY - 2022
Y1 - 2022
N2 - A type of spatial dependence might be suspected in the vehicle inspection data because it has similar characteristics with spatial data. This study aims to contribute to the establishment of a traffic operation order by revealing the spatial autocorrelation and by identifying regional characteristics that influence vehicle inspection failure rates. Based on the estimation of spatial econometric models, spatial dependence was found with a value of 0.37(Moran's I index), indicating that vehicle inspection data are spatially correlated. With respect to regional characteristics affecting vehicle inspection failure rates, five significant factors were identified: average vehicle age, average temperature, percentage of private inspection stations, percentage of diesel vehicles, and amount of precipitation. The results showed that differentiated vehicle inspections according to the characteristics of each region, such as strengthening automobile fuel filter inspections in areas with low average temperatures and strengthening emission inspections in regions with a high proportion of diesel vehicles, should be conducted.
AB - A type of spatial dependence might be suspected in the vehicle inspection data because it has similar characteristics with spatial data. This study aims to contribute to the establishment of a traffic operation order by revealing the spatial autocorrelation and by identifying regional characteristics that influence vehicle inspection failure rates. Based on the estimation of spatial econometric models, spatial dependence was found with a value of 0.37(Moran's I index), indicating that vehicle inspection data are spatially correlated. With respect to regional characteristics affecting vehicle inspection failure rates, five significant factors were identified: average vehicle age, average temperature, percentage of private inspection stations, percentage of diesel vehicles, and amount of precipitation. The results showed that differentiated vehicle inspections according to the characteristics of each region, such as strengthening automobile fuel filter inspections in areas with low average temperatures and strengthening emission inspections in regions with a high proportion of diesel vehicles, should be conducted.
KW - Failure
KW - Spatial autocorrelation
KW - Spatial regression
KW - Vehicle inspection
UR - http://www.scopus.com/inward/record.url?scp=85124215914&partnerID=8YFLogxK
U2 - 10.7467/KSAE.2022.30.1.019
DO - 10.7467/KSAE.2022.30.1.019
M3 - Article
AN - SCOPUS:85124215914
SN - 1225-6382
VL - 30
SP - 19
EP - 27
JO - Transactions of the Korean Society of Automotive Engineers
JF - Transactions of the Korean Society of Automotive Engineers
IS - 1
ER -