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Integration of Smart-Phone-Based Pavement Roughness Data Collection Tool with Asset Management System
With shrinking maintenance budgets and the need to do more with less, the need for accurate, robust asset management tools are greatly needed for the transportation engineering community. There are about 2.6 million paved public roads in the United States roadway network, and many transportation agencies utilize a pavement management system (PMS) to manage their pavement network in an efficient and cost-effective manner (Flintsch and McGhee 2009). PMSs require pavement roughness information along with other distress data. Pavement roughness is the deviation of pavement surface profile from planarity, which affects overall ride quality. Pavement roughness also slightly increases fuel consumption and therefore emission levels. Fuel consumption can be increased as much as 4-5 percent for very rough pavements (Klaubert 2001). Most transportation agencies use measures of the International Roughness Index (IRI) in planning maintenance and rehabilitation operations. Decades ago, roughness measurements were generally performed using manual equipment, such as a sliding straightedge. Technological advances have led to highly automated pavement condition assessments using sophisticated data collection vehicles equipped with sensitive inertial profilers.
Integration of Smart-Phone-Based Pavement Roughness Data Collection Tool with Asset Management System
With shrinking maintenance budgets and the need to do more with less, the need for accurate, robust asset management tools are greatly needed for the transportation engineering community. There are about 2.6 million paved public roads in the United States roadway network, and many transportation agencies utilize a pavement management system (PMS) to manage their pavement network in an efficient and cost-effective manner (Flintsch and McGhee 2009). PMSs require pavement roughness information along with other distress data. Pavement roughness is the deviation of pavement surface profile from planarity, which affects overall ride quality. Pavement roughness also slightly increases fuel consumption and therefore emission levels. Fuel consumption can be increased as much as 4-5 percent for very rough pavements (Klaubert 2001). Most transportation agencies use measures of the International Roughness Index (IRI) in planning maintenance and rehabilitation operations. Decades ago, roughness measurements were generally performed using manual equipment, such as a sliding straightedge. Technological advances have led to highly automated pavement condition assessments using sophisticated data collection vehicles equipped with sensitive inertial profilers.
Integration of Smart-Phone-Based Pavement Roughness Data Collection Tool with Asset Management System
W. G. Buttlar (Autor:in) / M. S. Islam (Autor:in)
2009
36 pages
Report
Keine Angabe
Englisch
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