In the past, highway authorities have selected pavement treatment type on the basis of the driving lane conditions and have applied the same treatment to all lanes. Recently, authorities started applying different treatments to the driving and passing lanes at different times. Because of costs, most highway authorities collect only the driving lane pavement condition data. Therefore, the passing lane pavement conditions need to be modeled with the driving lane data. To address this need, time series pavement condition and distress data along the driving and passing lanes of the Minnesota Road Research Project were obtained. The data were analyzed to develop and verify methodologies to estimate the passing lane conditions and distresses accurately with the use of the measured driving lane data. The methodologies are based on the fact that most pavement distresses are caused by material and environmental factors and by traffic loads. The effects of the first two factors are similar on adjacent driving and passing lanes. The differences in the conditions between adjacent lanes are mainly because of traffic distribution, which is expressed by the lane distribution factor. The developed methodologies use the measured pavement conditions along the driving lane and the lane distribution factors to estimate the time series conditions of the passing lane. For asphalt pavements, the time-dependent conditions of the passing lane can be accurately estimated (with low standard errors) with the measured conditions of the driving lane and the lane distribution factors. Procedural steps for implementing the methodologies are included.
Modeling Pavement Conditions of Multilane Roads with Measured Driving Lane Data
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 2304 , 1 ; 55-66
2012-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Modeling Pavement Conditions of Multilane Roads with Measured Driving Lane Data
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