Estimating the Effects of Pavement Condition on Vehicle Operating Costs (2012) / Chapter Skim
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Pages 40-50
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40 This chapter presents the methodology for developing vehicle repair and maintenance cost models using the two most promising models identified in this project: HDM 4 model and the model identified in the Texas Research and Development Foundation (TRDF) study (Zaniewski et al., 1982)
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41 extracted from Texas DOT and Michigan DOT databases (these data are presented in Appendix C)
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42 • Group A: roughness > 2.1 m/km (133.1 in./mi) • Group B: 1.9 m/km (120.5 in./mi)
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43 Updating Results of TRDF Study Texas and Michigan DOT data were first sorted by car make, model, and year. Then, only repair costs related to damage from vibrations were extracted (e.g., underbody inspection, axle repair and replacement, and shock absorber replacement)
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44 14,000 to 26,000 lb) based on the US DOT Vehicle Inventory and Use Survey classification.
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45 1979, Robson suggested the following model to generate the pavement surface roughness profiles, which was included in ISO 8608:1995: S k c ku n( )
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46 A simple generic linear numerical quarter-vehicle model was developed to compute the vertical vibration level of typical vehicle types from different pavement profiles at constant speeds. This numerical model, developed with the Matlab/ Simulink® programming environment, effectively computes the solution to the two-degrees-of-freedom system using the fixed-point method.
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47 Suspension Damage in Cars Figure 5-7 shows the damage accumulated in car suspensions after 160,000 km (100,000 mi) on a road with a given (constant)
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48 a given IRI level is calculated by dividing the accumulated damage corresponding to that IRI value (see Figure 5-7) by Dreplace and multiplying the result by $1,000.
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49 empirical approach using artificially generated profiles, and (3) the empirical approach (i.e., updated TRDF study)
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50 seems applicable to US conditions. All the models currently in use are empirical in nature, except for the VETO model, which is reported to yield predictions that are much higher than the actual costs observed in Sweden.
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