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Estimating the Effects of Pavement Condition on Vehicle Operating Costs (2012)

Chapter: Chapter 7 - Summary and Suggested Research

« Previous: Chapter 6 - Applicability to Emerging Technologies
Page 55
Suggested Citation:"Chapter 7 - Summary and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2012. Estimating the Effects of Pavement Condition on Vehicle Operating Costs. Washington, DC: The National Academies Press. doi: 10.17226/22808.
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Suggested Citation:"Chapter 7 - Summary and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2012. Estimating the Effects of Pavement Condition on Vehicle Operating Costs. Washington, DC: The National Academies Press. doi: 10.17226/22808.
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Suggested Citation:"Chapter 7 - Summary and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2012. Estimating the Effects of Pavement Condition on Vehicle Operating Costs. Washington, DC: The National Academies Press. doi: 10.17226/22808.
×
Page 57
Page 58
Suggested Citation:"Chapter 7 - Summary and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2012. Estimating the Effects of Pavement Condition on Vehicle Operating Costs. Washington, DC: The National Academies Press. doi: 10.17226/22808.
×
Page 58
Page 59
Suggested Citation:"Chapter 7 - Summary and Suggested Research." National Academies of Sciences, Engineering, and Medicine. 2012. Estimating the Effects of Pavement Condition on Vehicle Operating Costs. Washington, DC: The National Academies Press. doi: 10.17226/22808.
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55 Summary The objective of this research was to recommend models for estimating the effects of pavement conditions on vehicle operating costs. These effects are essential to sound planning and management of highway investments, especially under increasing infrastructure demands and declining budget resources. The recommended models reflect current vehicle technologies in the United States. The research focused on the cost components that are mostly affected by pavement conditions, namely, fuel consumption, repair and mainte- nance costs, and tire wear. The research does not include the effects of pavement conditions on changes in travel time, nor does it consider the safety-related or other implications of pavement conditions. To accomplish the objective of this research, several tasks were performed. First, a large amount of data and informa- tion was collected, reviewed, and analyzed to identify the most relevant VOC models. The review was focused on research that has identified factors affecting vehicle operating costs including pavement conditions. Next, a large field investiga- tion involving surveys to collect pavement condition data and field trials to collect fuel consumption and tire wear data were conducted. These data were used to calibrate and validate the HDM 4 fuel consumption and tire wear models for condi- tions in the United States and estimate the effects of pavement conditions on these components. The research also involved the collection of the repair and maintenance data of vehicle fleets from two departments of transportation (Michigan and Texas). The fleet data were used to update earlier research and develop mechanistic–empirical repair and maintenance mod- els that consider the paved surface conditions encountered in the United States and address the full range of vehicle types. Finally, an effort was made to consider how all these models would be impacted by emerging vehicle technologies. This study demonstrated that vehicle operating costs increase with pavement roughness for all classes of vehicles and types of pavements investigated. The most important cost components affected by roughness are fuel consumption followed by repair and maintenance, then tire wear. For fuel consumption, the most important factor is sur- face roughness (measured using IRI). An increase in IRI of 1 m/km (63.4 in./mi) will increase the fuel consumption of passenger cars by about 2% irrespective of speed. For heavy trucks, this increase is about 1% at normal highway speed (96 km/h or 60 mph) and about 2% at low speed (56 km/h or 35 mph). Surface texture (measured by MPD) and pave- ment type do not affect the fuel consumption of any vehicle class except for heavy trucks. An increase in MPD of 1 mm will increase fuel consumption by about 1.5% at 88 km/h (55 mph) and about 2% at 56 km/h (35 mph). For repair and maintenance, there is no effect of rough- ness up to IRI of 3 m/km. Beyond this range, an increase in IRI up to 4 m/km will increase repair and maintenance cost by 10% for passenger cars and heavy trucks. At IRI of 5 m/ km, this increase is up to 40% for passenger cars and 50% for heavy trucks. For tire wear, only the effect of roughness was considered. An increase in IRI of 1 m/km (63.4 in./mi) will increase the tire wear of passenger cars and heavy trucks by 1% at 88 km/h (55 mph). Fuel Consumption The effects of pavement conditions were investigated using five instrumented vehicles to measure fuel consumption over different pavement sections with different pavement condi- tions. These data were used to calibrate the HDM 4 fuel con- sumption model. The calibrated models were verified and were found to adequately predict the fuel consumption under dif- ferent operating, weather, and pavement conditions. Table 7-1 presents the predictions by the calibrated HDM 4. The increase in fuel consumption was computed from the baseline IRI of 1 m/km (63.4 in./mi). The table was generated at 17°C (62.6°F) when the MPD is 1 mm (0.04 in) and grade is 0%. C h a p t e r 7 Summary and Suggested Research

56 The analysis assumed that there is no interaction between the effect of roughness (unevenness) and surface texture given that their wavelength ranges are independent. The model showed pavement surface texture has an effect on fuel consumption only for heavier trucks. For example, a 1 mm decrease in MPD will result in a decrease in fuel consumption of 2.25% and 1.5% at 56 and 88 km/h (35 and 55 mph) speeds, respectively. Considering the significance of vehicle fuel consumption, the reduction of it is one of the main benefits that should be considered in technical and economic evaluations of road improvements. This research showed that a decrease in pave- ment roughness by 1 m/km (63.4 in./mi) will result in a 3% decrease in the fuel consumption for passenger cars. This decrease would save about 6 billion gallons of fuel per year of the 200 billion gallons consumed annually by the 255 million vehicles in the United States. With today’s gas prices, this fuel savings will amount to about $24 billion. Tire Wear The effects of pavement conditions on tire wear were investigated using field data. The HDM 4 tire wear model was calibrated to adequately predict the tire wear of passen- ger cars and articulated trucks. Table 7-2 presents the increase in tire wear as a function of IRI for all vehicle classes at 56, 88, and 112 km/h (35, 55, and 70 mph) caused by a change in IRI from the baseline condi- tion of 1 m/km (63.4 in./mi). The table was generated at 17°C (62.6°F) when the MPD is 1 mm (0.04 in) and the grade is 0%. These data show, for the same IRI value, that tire wear increases with increasing speed, and that the roughness effect is higher at higher speeds. This research showed that a decrease in pavement rough- ness by 1 m/km (63.4 in./mi) will result in about a 1% decrease in the tire wear for passenger cars. Assuming that the average annual kilometrage (mileage) for a passenger car is 24,000 km (15,000 mi), the average tire life is 72,000 km (45,000 mi), and the average price of a tire is $100, the 255 million vehicles will consume about $34.0 billion per year in tire wear cost. Therefore, a decrease in IRI by 1 m/km (63.4 in./mi) will save $340 million per year. Repair and Maintenance Two different approaches for estimating repair and mainte- nance costs induced by pavement roughness were developed: (1) an empirical approach that introduced adjustment factors to update the tables reported in an earlier study and (2) a mechanistic–empirical approach that involves fatigue damage analysis using numerical modeling of vehicle vibration response. The results from the mechanistic–empirical approach were compared to the empirical results and were found to be very close up to an IRI of 5 m/km (typical IRI range in the United States), with a standard error of about 2%. Table 7-3 lists the increase in repair and maintenance costs per kilometer for all vehicle classes due to an IRI increase from the baseline condition IRI of 1 m/km (63.4 in./mi) for pavements with 0% grade. A computer program was also developed to facilitate the use of the model. The program can be used to estimate repair and maintenance costs at the project and network levels. For project-level analysis, the actual road profile should be used to account for the effect of roughness features. The results show that there is no effect of roughness on repair and maintenance costs up to an IRI of 3 m/km. Beyond Speed Vehicle Class Fuel Consumption Base (mL/km) Adjustment Factors from the Base Value Base (mpg) Adjustment Factors from the Base Value IRI (m/km) IRI (m/km) 1 2 3 4 5 6 1 2 3 4 5 6 56 km/h (35 mph) Medium car 70.14 1.03 1.05 1.08 1.10 1.13 33.53 0.97 0.95 0.93 0.91 0.88 Van 76.99 1.01 1.02 1.03 1.04 1.05 30.55 0.99 0.98 0.97 0.96 0.95 SUV 78.69 1.02 1.05 1.07 1.09 1.12 29.89 0.98 0.95 0.93 0.92 0.89 Light truck 124.21 1.01 1.02 1.04 1.05 1.06 18.94 0.99 0.98 0.96 0.95 0.94 Articulated truck 273.41 1.02 1.04 1.07 1.09 1.11 8.60 0.98 0.96 0.93 0.92 0.90 88 km/h (55 mph) Medium car 83.38 1.03 1.05 1.08 1.10 1.13 28.21 0.97 0.95 0.93 0.91 0.88 Van 96.98 1.01 1.02 1.03 1.04 1.05 24.25 0.99 0.98 0.97 0.96 0.95 SUV 101.29 1.02 1.04 1.07 1.09 1.11 23.22 0.98 0.96 0.93 0.92 0.90 Light truck 180.18 1.01 1.02 1.03 1.04 1.05 13.05 0.99 0.98 0.97 0.96 0.95 Articulated truck 447.31 1.02 1.03 1.05 1.06 1.08 5.26 0.98 0.97 0.95 0.94 0.93 112 km/h (70 mph) Medium car 107.85 1.02 1.05 1.07 1.09 1.12 21.81 0.98 0.95 0.93 0.92 0.89 Van 128.96 1.01 1.02 1.03 1.03 1.04 18.24 0.99 0.98 0.97 0.97 0.96 SUV 140.49 1.02 1.04 1.06 1.08 1.10 16.74 0.98 0.96 0.94 0.93 0.91 Light truck 251.41 1.01 1.02 1.02 1.03 1.04 9.36 0.99 0.98 0.98 0.97 0.96 Articulated truck 656.11 1.01 1.02 1.04 1.05 1.06 3.58 0.99 0.98 0.96 0.95 0.94 Table 7-1. Effect of roughness on fuel consumption.

57 this range, an increase in IRI up to 4 m/km will increase repair and maintenance costs by 10% for passenger cars and heavy trucks. At an IRI of 5 m/km, this increase is up to 40% for passenger cars and 50% for heavy trucks. Assuming that the average annual kilometrage (mileage) for a passenger car is 24,000 km (15,000 mi), the repair and maintenance of the 255 million US vehicles will cost about $244.8 billion per year. Therefore, a decrease in IRI by 1 m/km (63.4 in./mi) will save $24.5 billion to $73.5 billion per year in repair and mainte- nance cost. As an example, assuming that about 14% of the US road network has an IRI higher than 3 m/km, the average annual Speed Vehicle Class (number of wheels) Tire Wear Baseline Conditions (%/km) Baseline Conditions (%/mi) Adjustment Factors from the Baseline Conditions IRI (m/km) 1 2 3 4 5 6 56 km/h (35 mph) Medium car (4) 0.0013 0.0021 1.01 1.01 1.02 1.02 1.03 Van (4) 0.0011 0.0017 1.00 1.01 1.01 1.02 1.02 SUV (4) 0.0011 0.0017 1.01 1.02 1.03 1.04 1.05 Light truck (4) 0.0012 0.0020 1.01 1.02 1.03 1.04 1.05 Articulated truck (18) 0.0006 0.0010 1.01 1.01 1.02 1.02 1.03 88 km/h (55 mph) Medium car (4) 0.0014 0.0022 1.01 1.02 1.03 1.04 1.05 Van (4) 0.0013 0.0021 1.01 1.01 1.02 1.03 1.04 SUV (4) 0.0013 0.0021 1.01 1.03 1.05 1.06 1.08 Light truck (4) 0.0018 0.0029 1.01 1.02 1.04 1.05 1.06 Articulated truck (18) 0.0007 0.0012 1.01 1.02 1.03 1.04 1.05 112 km/h (70 mph) Medium car (4) 0.0015 0.0025 1.01 1.03 1.04 1.06 1.08 Van (4) 0.0018 0.0028 1.01 1.02 1.03 1.04 1.04 SUV (4) 0.0017 0.0027 1.02 1.04 1.06 1.08 1.10 Light truck (4) 0.0029 0.0046 1.01 1.02 1.04 1.05 1.06 Articulated truck (18) 0.0009 0.0015 1.01 1.02 1.03 1.04 1.06 Table 7-2. Effect of roughness on tire wear rates. Speed Vehicle Class Repair and Maintenance Costs Average* ($/km) Average* ($/mi) Baseline Conditions ($/km) Baseline Conditions ($/mi) Adjustment Factors from the Baseline Conditions IRI (m/km) 1 2 3 4 5 6 56 km/h (35 mph) Medium car 0.040 0.064 0.015 0.024 1.0 1.0 1.1 1.4 1.7 Van 0.052 0.083 0.020 0.032 1.0 1.0 1.1 1.4 1.7 SUV 0.052 0.083 0.020 0.032 1.0 1.0 1.2 1.7 2.3 Light truck 0.058 0.092 0.021 0.034 1.0 1.0 1.2 1.7 2.2 Articulated truck 0.124 0.199 0.046 0.074 1.0 1.0 1.1 1.5 1.8 88 km/h (55 mph) Medium car 0.040 0.064 0.019 0.030 1.0 1.0 1.1 1.4 1.7 Van 0.052 0.083 0.025 0.040 1.0 1.0 1.1 1.4 1.7 SUV 0.052 0.083 0.025 0.040 1.0 1.0 1.2 1.7 2.3 Light truck 0.058 0.092 0.029 0.046 1.0 1.0 1.2 1.7 2.2 Articulated truck 0.124 0.199 0.063 0.101 1.0 1.0 1.1 1.5 1.8 112 km/h (70 mph) Medium car 0.040 0.064 0.023 0.036 1.0 1.0 1.1 1.4 1.7 Van 0.052 0.083 0.030 0.047 1.0 1.0 1.1 1.4 1.7 SUV 0.052 0.083 0.030 0.047 1.0 1.0 1.2 1.7 2.3 Light truck 0.058 0.092 0.035 0.057 1.0 1.0 1.2 1.7 2.2 Articulated truck 0.124 0.199 0.077 0.123 1.0 1.0 1.1 1.5 1.8 1 m/km = 63.4 in./mi *These costs are unit repair costs related only to damage from vibrations. Table 7-3. Effect of roughness on repair and maintenance costs.

58 Table 7-4. Unit costs. Vehicle Class Unit Costs Fuel Cost* ($/gal) Fuel Cost* ($/L) Tire Cost* ($/tire) Repair and Maintenance Costs ($/mi)† Repair and Maintenance Costs ($/km)† Small car $3.63 $0.96 $100 0.064 0.040 Medium car $3.63 $0.96 $100 0.064 0.040 Large car $3.63 $0.96 $100 0.064 0.040 Van $3.63 $0.96 $150 0.083 0.052 Four-wheel drive $3.63 $0.96 $150 0.083 0.052 Light truck $3.63 $0.96 $175 0.083 0.052 Medium truck $3.63 $0.96 $200 0.092 0.058 Heavy truck $3.97 $1.05 $250 0.119 0.074 Articulated truck $3.97 $1.05 $250 0.191 0.119 Mini bus $3.63 $0.96 $150 0.199 0.124 Light bus $3.63 $0.96 $175 0.083 0.052 Medium bus $3.97 $1.05 $200 0.092 0.058 Heavy bus $3.97 $1.05 $250 0.119 0.074 Coach $3.97 $1.05 $250 0.191 0.119 *These costs are estimates for 2011. †These costs are repair and maintenance costs caused by roughness only and are estimated based on data from 2007. Table 7-5. Effect of roughness on vehicle operating costs. Speed Vehicle Class Vehicle Operating Costs Baseline Conditions (¢/km) Baseline Conditions (¢/mi) Adjustment Factors from the Baseline Conditions IRI (m/km) 1 2 3 4 5 6 56 km/h (35 mph) Medium car 8.8 14.0 1.02 1.04 1.08 1.15 1.22 Van 10.0 16.1 1.01 1.02 1.05 1.11 1.18 SUV 10.2 16.3 1.02 1.03 1.09 1.20 1.34 Light truck 14.9 23.9 1.01 1.02 1.06 1.13 1.22 Articulated truck 36.1 57.7 1.02 1.03 1.07 1.13 1.19 88 km/h (55 mph) Medium car 10.5 16.8 1.02 1.04 1.08 1.15 1.22 Van 12.6 20.2 1.01 1.01 1.05 1.11 1.17 SUV 13.0 20.8 1.02 1.03 1.09 1.20 1.32 Light truck 21.6 34.6 1.01 1.02 1.05 1.12 1.20 Articulated truck 56.7 90.7 1.01 1.02 1.05 1.10 1.15 112 km/h (70 mph) Medium car 13.3 21.3 1.02 1.03 1.07 1.14 1.21 Van 16.5 26.5 1.01 1.01 1.04 1.10 1.16 SUV 17.6 28.2 1.01 1.03 1.08 1.18 1.29 Light truck 30.1 48.1 1.01 1.01 1.04 1.10 1.17 Articulated truck 81.2 130.0 1.01 1.02 1.04 1.08 1.13 1 m/km = 63.4 (in./mi) mileage for a passenger car is 24,000 km (15,000 mi), and a total of 255 million cars travel on the US road network, then the repair and maintenance cost for passenger cars in the United States would range from $15 billion to $25 bil- lion per year [for vehicle speeds ranging from 56 to 112 km/h (35 to 70 mph), respectively]. Table 7-4 lists the unit costs used in this study. Table 7-5 summarizes the change in vehicle operating costs per kilo- meter (mile) for all vehicle classes due to IRI changes from the baseline condition of 1 m/km (63.4 in./mi). These costs were computed using the default values. Applicability to Emerging Technologies Growing demand for fuel-efficient vehicles accelerated the research and development (R&D) efforts to meet this demand. New engine and combustion technologies, alternative fuels, vehicle design and maintenance, and tire technologies will

59 cycles, but it does not explicitly formulate the calculation of the constant. Further research is needed to incorporate the effect of congestion on fuel consumption. • In this study, the effect of pavement deflection/stiffness on fuel consumption was not investigated. Further research is needed to investigate this effect. • The mechanistic–empirical approach to estimate the effects of pavement conditions on repair and maintenance costs only involves passenger cars and articulated trucks. Then, it uses the results from an earlier study to estimate the costs for the other vehicle classes. Further research is needed to esti- mate quarter-car model parameters for other vehicle classes. • Since the tire wear field tests were conducted only for pas- senger cars and articulated trucks with conventional tires, tire wear field tests for other vehicle classifications and for emerging low fuel-consumption tires are needed. • The tire wear model could be improved by enhancing the modeling of tire–pavement interaction and loss of rubber due to friction. • This study focused on the effects of pavement conditions on fuel consumption, tire wear, and repair and mainte- nance costs. However, the research did not include the effects of pavement conditions on changes in travel time, nor did it consider the safety-related, environmental, or other implications of pavement conditions. Therefore, research is needed to investigate these effects. • The operation of trucks not only involves fuel, tire, and repair and maintenance costs but also the damage induced to the products during transportation. Further research will help estimate the effects of pavement conditions on damage to transported goods. • The fuel consumption model uses an empirical relation- ship between rolling resistance and IRI. The model could be further improved by developing a mechanistic formu- lation for predicting the effect of roughness on fuel con- sumption. For example, the vehicle models could be used to predict the dynamic load, which can then be used to replace the static weight in the model. affect vehicle operating costs. The effects of pavement con- ditions on vehicle operating costs will also be influenced by some of these technologies, specifically: • New engine technology: The HDM 4 model could be updated by changing the engine efficiency of vehicles to take into account these technologies. This study reports that new engine technologies will increase the engine efficiency by 5% to 12% and concludes that the effect of roughness on fuel con- sumption would likely be unaffected by these technologies. • Vehicle design: The HDM 4 model could be updated by changing the aerodynamic characteristics of vehicles to take into account these technologies. This study reports that, when introducing all aerodynamic improvements in one vehicle, the reduction in aerodynamic drag could be as much as 23%. Every 2% reduction in aerodynamic drag will result in a 1% improvement in fuel efficiency. • Automatic gear shift for heavy trucks could save as much as 10% in fuel consumption. • New tire technology: Use of the calibrated HDM 4 fuel and tire consumption model and the coefficients for new tires will help account for emerging tire technology. In addition, even though the new technologies will make vehicles more fuel efficient, the expenses of these technolo- gies relative to current vehicles will be higher. Some of the hardware involved with new technologies might be sensitive to vehicle vibration that would require more maintenance under rougher roads than current technologies. The work done in this study on repair and maintenance costs might offer a methodology to investigate this issue in the future. Suggested Research The results of this study lead to the following suggestions: • The fuel consumption model suggests a constant (dFuel) to take into account the effect of congestion and speed change

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TRB’s National Cooperative Highway Research Program (NCHRP) Report 720: Estimating the Effects of Pavement Condition on Vehicle Operating Costs presents models for estimating the effects of pavement condition on vehicle operating costs.

The models address fuel consumption, tire wear, and repair and maintenance costs and are presented as computational software that is included in the print version of the report in a CD-ROM format. The CD-ROM is also available for download from TRB’s website as an ISO image. Links to the ISO image and instructions for burning a CD-ROM from an ISO image are provided below.

Appendixes A through D to the report provide further elaboration on the work performed in the project that developed NCHRP Report 720. The appendixes, which were not included with the print version of the report, are only available for download through the link below.

• Appendix A: Fuel Consumption Models,

• Appendix B: Tire Wear Models,

• Appendix C: Repair and Maintenance Models, and

• Appendix D: An Overview of Emerging Technologies.

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CD-ROM Disclaimer - This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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