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The Development of Regression Models to Estimate Routine Maintenance Costs for State Highway Infrastructure

The Development of Regression Models to Estimate Routine Maintenance Costs for State Highway Infrastructure
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摘要 Literature review indicates that most studies on pavement management have been on reconstruction and rehabilitation, but not on maintenance;this includes routine, corrective and preventive maintenance. This study developed linear regression models to estimate the total maintenance cost and component costs for labor, materials, equipment, and stockpile. The data used in the model development were extracted from the pavement and maintenance management systems of the Nevada Department of Transportation (NDOT). The life cycle maintenance strategies adopted by NDOT for five maintenance prioritization categories were used as the basis for developing the regression models of this study. These regression models are specified for each stage of life-cycle maintenance strategies. The models indicate that age, traffic flow, elevation, type of maintenance, maintenance schedule, life cycle stage, and the districts where maintenances are performed all are important factors that influence the magnitude of the costs. Because these models have embedded the road conditions into the life-cycle stage and type of maintenance performed, they can be easily integrated into existing pavement management systems for implementation. Literature review indicates that most studies on pavement management have been on reconstruction and rehabilitation, but not on maintenance;this includes routine, corrective and preventive maintenance. This study developed linear regression models to estimate the total maintenance cost and component costs for labor, materials, equipment, and stockpile. The data used in the model development were extracted from the pavement and maintenance management systems of the Nevada Department of Transportation (NDOT). The life cycle maintenance strategies adopted by NDOT for five maintenance prioritization categories were used as the basis for developing the regression models of this study. These regression models are specified for each stage of life-cycle maintenance strategies. The models indicate that age, traffic flow, elevation, type of maintenance, maintenance schedule, life cycle stage, and the districts where maintenances are performed all are important factors that influence the magnitude of the costs. Because these models have embedded the road conditions into the life-cycle stage and type of maintenance performed, they can be easily integrated into existing pavement management systems for implementation.
作者 Hualiang (Harry) Teng Monika Hagood Yathi V. Yatheepan Yuyong Fu Haiqing Li Hualiang (Harry) Teng;Monika Hagood;Yathi V. Yatheepan;Yuyong Fu;Haiqing Li(Department of Civil and Environmental Engineering, University of Nevada, Las Vegas, USA;Nevada Department of Transportation, Carson City, USA;Tianjin Huaxia Architectural Design Co., Ltd., Tianjin, China;Transportation Institute of Inner Mongolia University, Hohhot, China)
出处 《Journal of Transportation Technologies》 2016年第5期339-359,共22页 交通科技期刊(英文)
关键词 Highway Infrastructure Routine Maintenance Regression Modeling Highway Infrastructure Routine Maintenance Regression Modeling
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