Traffic signs often convey critical information to drivers. To ensure visibility in nighttime or low light conditions, traffic signs must be in compliance with the minimum retrore- flectivity standards outlined by the...Traffic signs often convey critical information to drivers. To ensure visibility in nighttime or low light conditions, traffic signs must be in compliance with the minimum retrore- flectivity standards outlined by the manual on uniform traffic control devices （MUTCD）. Among all of the assessment methods （visual nighttime inspection, retroreflectivity measurement） and management methods （expected life, blanket replacement, and control signs） outlined in the MUTCD, expected sign life has been the most selected by agencies for maintaining compliance. In current literature, little research exists with regard to schedule sign replacement, focusing rather on the current favorite predictor, sign age. However, after collecting data on 1683 in-service traffic signs across the state of Utah, this study primarily concluded that not only sign age, but other contributing factors affect sign retroreflective performance. Aiming to determine the effects of various damage forms on sign retroreflectivity, statistical methods, including regression models, chi-square test, t- test, and odds ratio were employed to analyze traffic sign data. At the conclusion, the strong association between damage and retroreflectivity compliance of traffic signs was evident. In addition, to identify more critical damage forms, the effects of various forms on traffic sign retroreflectivity were compared. These conclusions provide insight to inform transportation agencies in the development of sign management plans and schedule sign replacement.展开更多
Among the different types of traffic sign damage, vandalism is exclusively caused by humans. Traffic sign vandalism is a serious concern, since it can lead to an increase in unsafe driving behaviors. In addition, it r...Among the different types of traffic sign damage, vandalism is exclusively caused by humans. Traffic sign vandalism is a serious concern, since it can lead to an increase in unsafe driving behaviors. In addition, it results in increased costs to transportation agencies to replace, repair, or maintain the vandalized signs. This paper examines the association between the local population demographics and traffic sign vandalism rates in the State of Utah. To accomplish this goal, sign data of over 97,000 traffic signs across Utah were digitally collected by an equipped vehicle. Sign damage data were obtained from the inspection of daytime digital images taken of each individual sign. Demographic data of Utah＇s counties, including population density, ethnicity, age, income, education, and gender, were obtained from the U.S. Census. The association between demographic groups and vandalism rates was tested using chi-square and trend tests. The results reveal that the most statistically significant variables comprise median household income, completion of at least an associate degree, and population density. According to the fitted linear regression model, a relationship exists between sign vandalism rate and local population demographic. The findings of this investigation can assist transportation agencies in identifying areas with a higher likelihood of sign vandalism, based on demographic characteristics. Such information can then be used to encourage scheduled sign inspections and to implement various countermeasures to prevent sign vandalism.展开更多
文摘Traffic signs often convey critical information to drivers. To ensure visibility in nighttime or low light conditions, traffic signs must be in compliance with the minimum retrore- flectivity standards outlined by the manual on uniform traffic control devices （MUTCD）. Among all of the assessment methods （visual nighttime inspection, retroreflectivity measurement） and management methods （expected life, blanket replacement, and control signs） outlined in the MUTCD, expected sign life has been the most selected by agencies for maintaining compliance. In current literature, little research exists with regard to schedule sign replacement, focusing rather on the current favorite predictor, sign age. However, after collecting data on 1683 in-service traffic signs across the state of Utah, this study primarily concluded that not only sign age, but other contributing factors affect sign retroreflective performance. Aiming to determine the effects of various damage forms on sign retroreflectivity, statistical methods, including regression models, chi-square test, t- test, and odds ratio were employed to analyze traffic sign data. At the conclusion, the strong association between damage and retroreflectivity compliance of traffic signs was evident. In addition, to identify more critical damage forms, the effects of various forms on traffic sign retroreflectivity were compared. These conclusions provide insight to inform transportation agencies in the development of sign management plans and schedule sign replacement.
文摘Among the different types of traffic sign damage, vandalism is exclusively caused by humans. Traffic sign vandalism is a serious concern, since it can lead to an increase in unsafe driving behaviors. In addition, it results in increased costs to transportation agencies to replace, repair, or maintain the vandalized signs. This paper examines the association between the local population demographics and traffic sign vandalism rates in the State of Utah. To accomplish this goal, sign data of over 97,000 traffic signs across Utah were digitally collected by an equipped vehicle. Sign damage data were obtained from the inspection of daytime digital images taken of each individual sign. Demographic data of Utah＇s counties, including population density, ethnicity, age, income, education, and gender, were obtained from the U.S. Census. The association between demographic groups and vandalism rates was tested using chi-square and trend tests. The results reveal that the most statistically significant variables comprise median household income, completion of at least an associate degree, and population density. According to the fitted linear regression model, a relationship exists between sign vandalism rate and local population demographic. The findings of this investigation can assist transportation agencies in identifying areas with a higher likelihood of sign vandalism, based on demographic characteristics. Such information can then be used to encourage scheduled sign inspections and to implement various countermeasures to prevent sign vandalism.
