5. Vehicle operating cost (VOC) models

5.1 Background

Vehicle operating costs are an important component of cost-benefit analysis and they are required to be estimated for the full vehicle fleet, and for different operating conditions.

Different methods exist and have been developed through various Austroads studies. There has been a stated requirement to provide models that possess the following attribute, and that can be applied and updated in a clear and consistent manner:

  • To better accommodate changes in vehicle technology and a changing vehicle fleet, including under different loading conditions and regulations
  • To be amenable for application across networks subject to uninterrupted and interrupted/stop-start conditions
  • To be capable of application to general cost-benefit analysis studies at a network level and for major capital projects, including employing the results of traditional 4–5 stage transport models.

This chapter of the Guidelines describes the background to how models have evolved in the last 20 years and provides a recommended set of models and guidance on their application consistent with the above requirements.

In aiming to meet the first requirement, a number of choices exist, including:

  • ‘Mechanistic-empirical’ model forms, which estimate resource consumption in terms of the underlying physics and mechanical engineering processes and can be adapted to suit a range of fleet and road operating conditions. The HDM-III (Watanadada et al., 1987) and HDM-4 (Bennett & Greenwood, 2006 and Stannard & Wightman, 2006) models are of this kind and are structured in a mechanistic form, with the coefficients derived by the statistical analysis of observations. The latest models utilise the Australian-developed ARFCOM fuel consumption model (Biggs, 1988). The speed models have been calibrated to driver behaviour and the response of the mechanistic models using results of comprehensive speed studies undertaken in Australia in the late 1990s and early 2000s. The maintenance and spare parts models are also based on field observations in Australia (Thoresen & Roper, 1999). New Zealand studies (OPUS International Consultants, 1999), which form the basis for the NZ economic evaluation manual (NZ Transport Agency, 2013) and further Austroads studies (Austroads, 2012b and Tan et al.. 2012) have also confirmed the suitability of the models. Whereas these models were originally derived for application in non-urban conditions, they have been adapted for use in urban and stop-start environments as a result of Austroads funded studies (Cox & Arup, 1996 and Thoresen, 2004).
  • Regression equation type models, often described as ‘statistical’ models, where the structure does not seek to emulate the mechanical engineering processes. While these models can provide reasonable results for applications which are close to the original derivation of the models, including the scope and combination of parameters and parameter values tested, this also limits their potential application. These models were amongst the first used for VOC estimation, such as those derived by Hodges et al. (1975), and a number of the original NIMPAC models (Both & Bayley, 1976) were of this kind. The derivation of the NIMPAC models followed the extensive efforts undertaken in Australia to develop methodologies capable of estimating RUCs and their sensitivity to road conditions in both non-urban and urban settings. Work commenced in the late 1960s, largely initiated by the former Commonwealth Bureau of Roads, and proceeded through the 1970s and 1980s under NAASRA.

Either of the above models may be employed to produce more user friendly formats, either as a suite of tables or as a set of derived equations based on specific operating conditions and vehicle related assumptions.

In Australia, achieving consistency between different rural/uninterrupted flow models has previously been the subject of a harmonisation process where algorithms, procedures and values could be used by agencies to benchmark their models to agreed costs and technologies. This culminated in an Austroads Road User Cost Steering Group (RUCSG) program covering the period 1994‒2005 (Peters, 2001). The program provided the basis to calibrate models such as NIMPAC and RURAL (Both & Bayley, 1976), which formed the basis of the evaluation procedures of road agencies, to estimate similar values as the ‘mechanistic-empirical’ models. An example of the technical documents that contained parameter values in a set of lookup tables is provided in Thoresen and Roper (1996). These continue to provide the basis for evaluation models in use in Australia at present, with the output of the ‘mechanistic‑empirical’ models now used as the benchmark.

However, since the mid-2000s, improvements of rural RUC estimation methodologies in Australia have been ad hoc or have been undertaken as part of non-VOC dedicated projects (Michel et al., 2008). As a consequence, practitioners have been challenged in remaining up-to-date with developments. Notably, the parameter values and tables used in current road agency models have benefited from the outputs of the harmonisation process

In meeting the second requirement, Austroads material on urban VOC models extends over a significant period of time, with developments in the specifications of the model. This is reflected in Lloyd and Tsolakis (2000), for example, which provides an overview of urban road user cost (RUC) models, as well as addressing the issue of harmonisation of such models. It describes the Traffic Modelling System (TRAMS) model developed for Western Australia, based mainly on NIMPAC models with the ARRB ARFCOM fuel consumption model. However, the model was never adopted across jurisdictions in Australia, although NIMPAC has been the basis for models in Australia while ARFCOM remains the basis of fuel consumption models in Australia as well.

Austroads (2004) presented an alternative urban stop-start model and a freeway (uninterrupted flow) models on a per trip basis. This drew on the studies by Austroads reported by Cox and Arup (1996). The models initially employed an adaptation of the HDM-III and ARFCOM models for urban conditions, with the final models based on use of Australianised HDM-4 models. The performance estimates for vehicle maintenance and spare parts, tyre consumption, and fuel and oil consumption based on applying multiplicative factors or alternative models to produce estimates for urban conditions. Capital depreciation and interest is accounted for through reduced fleet utilisation because of the lower journey speeds. The free flow version of these models is consistent with the earlier mentioned rural uninterrupted flow models, thus offering the potential for consistency in VOC and RUC estimation across different parts of the network.

In Austroads (2005a) and Austroads (2008), the approach taken was to provide models for ‘at grade’ and freeway models (Austroads 2008) for all day average speeds, including representative traffic conditions, with model parameters produced on the basis of outputs from the TRAM. This approach has formed the basis of VOC models presented in recent updates (Austroads, 2012) and Austroads (2008). Austroads (2012) involved the aggregation of RUC components (VOC added to travel time), whereas earlier updates had presented coefficients for VOC both excluding travel time and then including travel time (vehicle occupants and freight travel time). This has been identified as an area that required disaggregation of VOC (i.e. excluding travel time).

However, the latter models have proved difficult to calibrate for urban conditions, with some practitioners, such as TfNSW in their VEHOP model (TfNSW, 2013b), preferring to use the models developed in Austroads (2004). The presentation of a set of VOCs excluding travel time has also been a key objective that has directed the review of parameter values for the ATAP Guidelines review, with an objective of obtaining cost data for VOC components (excluding travel time) for urban stop-start conditions and freeway models.

In addressing the third requirement, consideration has been given to the operating conditions and modelling complexity that can be reasonably modelled for cost-benefit analysis purposes. In particular, under interrupted flow conditions performance is highly dependent on factors such as traffic volume and mix, road configuration, geometry and layout (and therefore capacity and speed), intersection types and spacing (including the provision of graded separated or at grade intersections), and signal controlled intersections. A number of these factors are directly accounted for in current CBA oriented modelling. However, the level of complexity that is possible and reasonable for such applications requires consideration.

Bowyer et al. (1985) offered a classification of urban fuel consumption modelling that provides an insight to the complexity of the problem, with the physical estimates drawing on performance models such as the ARRB ARFCOM fuel consumption model (Biggs, 1988), and the modelling framework reflected in software such as aaSIDRA (see Akcelik & Besley, 2003). The classification is as follows:

  • Instantaneous models (traffic management schemes, individual road sections, individual intersections, small networks where instantaneous speed data is available)
  • Elemental models (incorporating four elements of cruise, idle, acceleration, deceleration). Same application as instantaneous, but used where only speed data are available for elements (modified for non-urban application)
  • Running speed models. Travel is split into running and stopped components. Use at a trip level but not for traffic management modelling. Trip length > 1km
  • Average travel speed model. Travel speed includes stop time. Used for large scale transport modelling, including traditional 4‒5 stage component models. Accurate for average travel speeds < 50 km/h.

The average travel speed model, based on the total time on a link calculated as the sum of the time to traverse a link at the estimated operating speed based on speed‑flow considerations and the intersection delay, is considered as a suitable basis for CBA. This method was also employed by Cox and Arup (1996), and in both the preceding and subsequent studies that underpinned the Austroads (2004) urban stop‑start model and a freeway (uninterrupted flow) model. These models also adopt the mechanistic-empirical VOC models used to benchmark other model variants and incorporate the ARRB ARFCOM model, which remains the core of fuel consumption models in Australia for both urban and non-urban conditions. Use of this method also provides a consistent approach to incorporating travel time and freight delay costs, including modelling on the basis of different time periods, such as a.m. and p.m. peak periods, and day and night time off-peak periods. This provides a clearly defined and generic basis for general CBA with total RUC calculated using a common average travel speed/total link time.

The following sections describe the scope of both uninterrupted flow and interrupted flow models that use the mechanistic-empirical models and average travel speed approach, with this being consistent with Austroads (2004), TfNSW (2013b) and NZ Transport Agency (2013) for the purposes of general CBA. This provides a preferred model, while noting that other models exist and could justifiably be used.

5.2 Vehicle classification in Australia

The vehicle types included in the analysis follow the 20 vehicle classification (Thoresen & Ronald, 2002) subsequently used in HDM-4 in Australia, as well as the Austroads 12 bin classification (Austroads, 2002 and most recently Austroads, 2013b) as far as possible. The use of this vehicle classification in the ATAP Guidelines aims to provide practitioners with as wide a range of vehicle types as possible from which the appropriate vehicle types can be selected for their analysis. These vehicle types, as well as their assumed vehicle weights, payloads, pavement damage factors in equivalent standard axles (ESA)[1]and passenger car equivalent units (PCUs) are presented in Table 5.1. An overview of the vehicle classifications used in Australia and their basis over time is described in Appendix C.

Table 24: Vehicle parameters for vehicle types used in ATAP VOC modelling
Vehicle typeGCM(tonnes)Maximum payload (tonnes)ESAs per vehicle at 75% payloadESAs per vehicle at 100% payloadESAs per vehicle at 125% payloadEngine
power (kw)
Annual
km
PCU / PCSE[2]
01. Small Car 1.2 0.4 0.0002 0.0003 0.0004 65 23,000 0.99
02. Medium Car 1.4 0.4 0.0005 0.0006 0.0006 80 23,000 1
03. Large Car 1.6 0.4 0.0008 0.0010 0.0011 110 23,000 1.01
04. Courier Van-Utility 2.15 0.85 0.0024 0.0031 0.0039 60 30,000 1.11
05. 4WD Mid Size Petrol 2.73 0.93 0.0066 0.0081 0.0097 132 30,000 1.12
06. Light Rigid 3.75 2.15 0.01 0.01 0.02 56 30,000 1.23
07. Medium Rigid 10.4 7.2 0.53 0.69 1.28 130 40,000 1.4
08. Heavy Rigid 22.5 13.5 2.72 3.59 6.17 190 86,000 1.56
09. Heavy Bus 19 7 1.17 2.32 3.51 200 70,000 1.59
10. Artic 4 Axle 31.5 20.5 3.96 5.07 8.95 190 86,000 1.78
11. Artic 5 Axle 39 26 4.4 5.65 10.08 260 86,000 1.84
12. Artic 6 Axle 42.5 27.5 3.89 4.97 8.54 300 86,000 1.89
13. Rigid + 5 Axle Dog 59 40 5.44 7.04 12.65 320 86,000 1.92
14. B-Double 62.5 40.5 4.93 6.35 11.02 350 86,000 2.22
15. Twin steer + 5 Axle Dog 64 43 4.49 7.58 13.66 360 86,000 1.97
16. A-Double 79 48 6.5 8.42 14.34 370 86,000 2.75
17. B Triple 82.5 48.5 5.99 7.73 12.88 380 86,000 2.82
18. A B Combination 99 60 7.54 9.80 16.73 380 86,000 2.9
19. A-Triple 115.5 71.5 9.1 11.86 20.61 390 86,000 3.38
20. Double B-Double 119 72 8.59 11.18 19.13 400 86,000 3.38

Source: ARRB Group Ltd.

5.3 Uninterrupted flow VOC models

5.3.1 Basis of the uninterrupted flow VOC models

The development of a suite of models that can be used by a variety of different user types in an uninterrupted flow, typically rural and freeway, environment sought to provide the practitioner with the ability to either:

  • Populate a simplified road user cost model with appropriate variables and associated coefficients, or
  • Generate a series of tables with appropriate unit cost values that can serve as a ‘ready reference’ of rural VOC for analysis or a benchmark to calibrate the models used by practitioners.

The simplified model was developed by employing the Australianised HDM-4 VOC models to generate estimates of VOC for a wide range of vehicles and operating conditions, and using this data as input for developing multiple regression equations. These were applied in populating the tables of values.

The underlying VOC component models have been the subject of extensive calibration studies. This has led to the development of an Austroads harmonised version with a vehicle fleet and model configuration specifically created for application in Australia.

A number of simplified, aggregate models, which have been derived using the outputs of a structured analysis, are available from several sources. The resulting models comprise a multi-variate regression equation that includes a number of terms, with parameters and coefficients. The model is generated by first defining and running a series of analysis cases and using the raw outputs to subsequently derive coefficients through regression analysis of multiple HDM-4 outputs.

Several model specifications were considered, specifically the following.

ARRB aggregate model

ARRB developed an aggregate model based on regression of HDM-III, and later HDM-4, outputs for use in the Pavement Life Cycle Costing (PLCC) tool (Linard et al., 1996). This model was later applied in the Freight and Mass Limits Tool (FAMLIT) (Michel & Hassan et al., 2008). Separate sets of coefficients were estimated for each vehicle type. Vehicle speed was not used as an input or output, but is inherent in the model set up where the speed is estimated internally based on a separate free or desired speed model. This model draws on Australian studies and is consistent with design guidance and real life observations, and is structured as follows:

VOC = a1*(1 + a2*NRM + a3*Rise&Fall + a4*Curvature + a5 *Payload)

where:

VOC = vehicle operating costs in cents per km

NRM = road roughness in NAASRA counts per km

Rise&Fall = the cumulative sum of all rises and falls in m/km

Curvature = the accumulated curvature in degrees/km

Payload = the weight of good carried, i.e. above tare weight, in kg

a1 to a5 = model coefficients.

Alternative aggregate model

An alternative aggregate model reported by Phedonos (2006) and applied in international studies by ARRB and by the NZ Transport Agency (2013) produces a base set of VOC’s and a set of coefficients that uses speed and roughness as key input parameters, as follows:

VOC = BaseVOC * [k1 + k2/V + k3*V 2 + k4*IRI + k5*IRI 2]

where:

BaseVOC = lowest VOC point in curve from raw HDM-4 output

V = Vehicle speed in km/h

IRI = International Roughness Index in m/km

k1 to k5 = model coefficients.

In order to generate the models, ranges of various attributes were selected to represent the breadth of operating conditions, including:

  • Rise and fall and curvature
  • Road roughness
  • Road widths
  • Vehicle types, weights and payloads parameters.

Typical assumptions for gradient and curvature have not changed since Thoresen and Roper (1996) and the categories typically used together are set out in Table 5.2 and have also been used in the analysis of uninterrupted flow VOC presented in this report:

Table 25: Gradient and curvature categories assumed for road stereotypes in Australia
VariableCategories
Gradient (Rise & Fall) Flat (0%), 4%, 6%, 8% & 10%
Curvature (Terrain type) Straight (20°/km)

Curvy / Hilly / Winding (120°/km) &

Very Curvy or Very Winding (300–320°/km)

As one of the most important determinants of VOCs, the relationship between VOC and road roughness was examined in detail in Austroads (2012b) and Tan et al. (2012). The study found that international and local reviews (e.g. Thoresen, 2004) confirmed a varied but positive relationship between VOC-roughness in terms of all VOC components, especially in Australian conditions at levels of 1.2–5.8 IRI[3]:

  • Fuel consumption (indeterminate direction, varies with the roughness level)
  • Repairs and maintenance costs
  • Tyre wear
  • Lubricating oil costs.

Ranges of road roughness were tested starting from a value of 2 IRI, with outputs produced at 1 IRI increments up to 11 IRI.

Road widths assumed for the purposes of VOC modelling were identified as the most typical that may result in differences in VOC and are listed below:

  • 4.5m
  • 5.8m
  • 8.5m.

Road widths below 4.5m were deemed to comprise a small portion of the road network and so were not included, while road widths below 8.5m did not result in significant increases in speed and changes in VOC.

5.3.2 Recommended model structure and coefficients

Two models were developed, namely for total VOC (including fuel consumption) and for fuel consumption.

Structure and coefficients for uninterrupted flow VOC model

The total VOC model is as follows, with coefficient values for a sample of the relationships shown in Table 5.3 and a full set of values presented in Appendix D:

VOC = BaseVOC * (k1 + k2/V + k3*V2 + k4*IRI + k5*IRI2 + k6*GVM)

where:

VOC, vehicle operating costs in cents/km

BaseVOC = lowest VOC point in curve from raw HDM-4 output

V = Vehicle speed in km/h

IRI = International Roughness Index in m/km

GVM = gross vehicle mass in tonnes

k1 to k6 = model coefficients.

Table 26: Example coefficients for rural (uninterrupted/free flow speed) VOC model (cents per km)
Vehicle typeBase VOC (cents/km)K1K2K3K4K5K6
01. Small Car 21.65553 0.682568 8.926626 1.86E-05 0.029245 0.000812 0.040681
02. Medium Car 28.58679 0.689129 10.27355 1.43E-05 0.027139 0.000945 0.030451
03. Large Car 37.23451 0.714542 10.81935 1.09E-05 0.023979 0.001031 0.020684
04. Courier Van-Utility 32.14678 0.671992 8.085664 1.53E-05 0.039596 0.002492 0.023847
05. 4WD Mid Size Petrol 35.49258 0.704089 7.16007 1.45E-05 0.034579 0.0021 0.0163
06. Light Rigid 44.70851 0.690409 5.571115 2.38E-05 0.042392 0.001879 0.013114
07. Medium Rigid 51.70626 0.64653 8.310133 2.08E-05 0.037528 0.001762 0.010923
08. Heavy Rigid 64.34463 0.45218 10.40255 3.42E-05 0.082007 0.000232 0.006585
09. Heavy Bus 100.1854 0.599271 9.039805 1.14E-05 0.066026 0.001052 0.004438
10. Artic 4 Axle 86.46287 0.443656 9.169067 3.51E-05 0.087456 0.000257 0.006451
11. Artic 5 Axle 95.65238 0.48678 8.851208 3.03E-05 0.083934 0.000404 0.004411
12. Artic 6 Axle 103.6022 0.491922 8.586421 2.8E-05 0.085237 0.000367 0.004082
13. Rigid + 5 Axle Dog 109.6991 0.507333 7.403231 2.75E-05 0.081194 0.000107 0.003943
14. B-Double 121.4093 0.483655 7.876344 2.41E-05 0.091051 0.000148 0.003567
15. Twin steer + 5 Axle Dog 120.4225 0.501057 7.606813 2.45E-05 0.085776 0.000191 0.003593
16. A-Double 146.9991 0.477559 7.54018 1.95E-05 0.096147 8.86E-05 0.002989
17. B Triple 170.3634 0.488334 7.864302 1.58E-05 0.097835 0.000332 0.00258
18. A B Combination 166.3673 0.475805 7.006039 1.75E-05 0.09811 -5.2E-05 0.002671
19. A-Triple 186.8652 0.480136 6.884288 1.56E-05 0.099253 -2E-05 0.002393
20. Double B-Double 189.7076 0.479935 6.579042 1.57E-05 0.098984 -0.00013 0.002361

RF = 0

Curvature = 20° / km

Source: ARRB Group Ltd.

Road width is not a required input assumption because it only affects the estimated VOC (or fuel consumption) through the speed of travel, which is a user supplied input.

Structure and coefficients of the uninterrupted fuel consumption model

The fuel consumption model is as follows, with coefficient values for a sample of the relationships shown in Appendix E.

Fuel consumption (litres/km) = BaseFuel * (k1 + k2/V + k3*V2 + k4*IRI + k5*GVM)

BaseFuel = lowest fuel consumption point in curve from raw HDM-4 output

V = Vehicle speed in km/h

IRI = International Roughness Index in m/km

GVM = gross vehicle mass in tonnes

k1 to k5 = model coefficients.

The tables of parameters are extensive since they have been defined for different horizontal curvature and rise and fall value.

An example of the coefficients estimated for the model specified above is contained in Table 5.4.

Table 27: Example coefficients for rural (uninterrupted/free flow speed) fuel consumption model (litres per 100 km)
Vehicle typeBase fuel consumption (litres/100km)K1K2K3K4K5

01. Small Car

6.419556

0.441226

12.43718

6.68E-05

0.006151

0.149391

02. Medium Car

7.771756

0.429248

14.42872

5.78E-05

0.005364

0.122652

03. Large Car

9.826507

0.473008

15.01703

4.7E-05

0.004258

0.08713

04. Courier Van-Utility

7.609467

0.284026

19.36752

6.91E-05

0.006175

0.110658

05. 4WD Mid Size Petrol

10.24522

0.464267

14.11609

5.05E-05

0.005148

0.063315

06. Light Rigid

8.085994

0.239071

13.9732

0.000116

0.012785

0.099828

07. Medium Rigid

12.45859

0.36312

9.564724

9.97E-05

0.014856

0.048677

08. Heavy Rigid

23.22869

0.243735

14.52463

9.95E-05

0.012912

0.019901

09. Heavy Bus

23.33246

0.271022

14.12877

6.85E-05

0.011434

0.01995

10. Artic 4 Axle

27.24712

0.160111

12.59432

0.000116

0.019467

0.021969

11. Artic 5 Axle

30.44964

0.265547

11.51051

0.000103

0.017613

0.014919

12. Artic 6 Axle

33.79927

0.303256

10.38151

9.34E-05

0.017999

0.013406

13. Rigid + 5 Axle Dog

38.14329

0.302384

9.066662

8.58E-05

0.02207

0.011962

14. B-Double

41.48179

0.32033

8.323599

7.96E-05

0.022113

0.010988

15. Twin steer + 5 Axle Dog

40.98332

0.321609

8.44159

8.01E-05

0.022176

0.011101

16. A-Double

47.75104

0.300993

7.10185

7.17E-05

0.024567

0.009609

17. B Triple

50.31407

0.30429

6.703995

6.89E-05

0.024871

0.009132

18. A B Combination

54.29232

0.287536

6.08939

6.64E-05

0.027662

0.008529

19. A-Triple

58.66595

0.27658

5.547481

6.39E-05

0.029925

0.00794

20. Double B-Double

61.23917

0.280027

5.283165

6.2E-05

0.029966

0.007613

RF = 0

Curvature = 20° / km

Source: ARRB Group Ltd.

5.3.3 Updated uninterrupted (free flow) speed vehicle operating costs for Australia as at 2013

For practitioners who wish to use tables of values, Tables 5.3 through 5.8 contain updated uninterrupted (free flow) speed, VOC (cents per km) and fuel (litres per 100 km) data using the most recent unit values (June 2013) for selected vehicle types based on Austroads (2005a). Applicable speeds were derived from NIMPAC and HDM approaches and VOC and fuel consumption outputs calibrated to those speeds for appropriate vehicle types.

A roughness level of 2 IRI was assumed for the rural VOC modelling analysis, with an assumed 75% payload for freight vehicles. Other VOC estimates can be made applying the model specified and adjusting appropriately for payload.

A full set of values for VOC and fuel consumption for the 20 vehicle classification can be estimated using the appropriate coefficients in Table 5.3 and Table 5.4.

Table 28: Free speed (km/h) tables for rural (uninterrupted/free flow speed) roads (NIMPAC model speeds)
% GradientCurvatureMedium carRigid trucks
 LCV
(2 axle 4 tyre)  
Light truck
(2 axle 6 tyre)  
Medium truck
(2 axle 6 tyre)
Heavy truck
(3 axles)
Large bus
(3 axles)
Articulated truck
(6 axle)
B-Double
(9 axles)
Road widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad width
4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m
Flat Straight 83 105 110 75 92 96 80 89 95 83 95 100 83 95 100 86 100 106 88 100 105 86 100 110
Curvy 77 90 93 68 78 80 71 77 80 74 81 83 73 80 82 71 75 77 72 75 76 77 85 89
Very curvy 69 75 76 60 66 67 63 66 67 65 68 70 64 67 68 59 60 60 59 60 60 67 70 72
4 Straight 82 102 106 72 86 88 74 81 86 70 76 79 65 69 71 49 52 53 38 40 41 72 78 82
Curvy 76 89 90 66 74 76 67 72 74 65 69 70 60 63 64 45 47 47 35 36 36 67 71 73
Very curvy 68 74 75 59 64 65 60 63 64 59 62 62 55 57 58 41 42 42 32 33 33 61 63 64
6 Straight 76 88 90 65 73 74 64 68 70 57 59 60 50 52 52 39 40 40 27 28 28 57 59 60
Curvy 72 81 82 61 66 67 60 63 64 54 56 57 49 50 50 38 39 39 27 27 27 55 57 58
Very curvy 66 71 71 56 60 60 55 57 58 51 53 53 46 47 47 36 36 36 26 26 26 53 54 54
8 Straight 66 72 72 56 59 60 53 55 55 45 46 46 40 40 40 32 32 32 20 20 20 45 46 46
Curvy 64 68 69 53 56 57 51 53 53 44 45 45 39 39 39 32 32 32 19 19 19 45 45 46
Very curvy 60 63 63 50 53 53 49 50 50 43 44 44 38 38 38 31 31 31 19 19 19 44 44 44
10 Straight 56 59 59 47 49 49 44 45 45 36 36 36 32 32 32 24 24 24 16 16 16 37 37 37
Curvy 55 57 58 46 47 48 43 44 44 36 36 36 32 32 32 24 24 24 16 16 16 37 37 37
Very curvy 53 55 55 44 46 46 42 43 43 36 36 36 32 32 32 24 24 24 16 16 16 36 36 37

Roughness = 2 IRI

Vehicle loading = 75% of vehicle payload

Source: ARRB Group Ltd.

Table 29: Vehicle operating cost (cents per km) for rural (uninterrupted/free flow speed) roads, June $2013 (NIMPAC model speeds)
% GradientCurvatureMedium carRigid trucks
 LCV
(2 axle 4 tyre)  
Light truck
(2 axle 6 tyre)  
Medium truck
(2 axle 6 tyre)
Heavy truck
(3 axles)
Large bus
(3 axles)
Articulated truck
(6 axle)
B-Double
(9 axles)
Road widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad width
4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m
Flat Straight 28.8 29.8 30.1 32.2 33.0 33.2 46.8 48.1 49.1 55.1 56.8 57.6 71.0 74.7 76.5 100.4 101.9 102.8 116.4 121.7 124.3 136.3 142.4 147.6
Curvy 28.7 29.0 29.2 32.1 32.4 32.5 45.8 46.4 46.8 54.8 55.6 55.8 69.6 71.4 72.0 100.6 100.7 100.8 111.9 112.8 113.1 135.0 138.1 139.9
Very curvy 28.8 28.8 28.8 32.4 32.5 32.5 45.5 45.8 45.9 56.3 56.8 57.2 71.5 72.5 72.9 103.5 103.5 103.5 113.2 113.5 113.5 140.4 142.2 143.5
4 Straight 29.1 29.8 30.0 33.0 33.3 33.3 47.8 48.4 49.0 59.1 59.2 59.3 85.9 85.7 85.6 120.5 119.4 119.1 151.7 150.7 150.3 186.2 186.1 186.1
Curvy 29.0 29.3 29.3 33.1 33.1 33.1 47.2 47.4 47.6 59.3 59.2 59.2 86.4 86.1 86.1 122.2 121.4 121.4 154.2 153.6 153.6 187.9 187.7 187.7
Very curvy 29.2 29.1 29.1 33.4 33.3 33.3 47.1 47.1 47.2 60.2 60.1 60.1 87.8 87.6 87.5 124.4 124.0 124.0 157.0 156.4 156.4 190.6 190.5 190.5
6 Straight 29.5 29.6 29.7 34.8 34.5 34.5 50.0 50.1 50.1 66.3 66.2 66.1 106.7 106.3 106.3 140.6 140.0 140.0 196.6 195.4 195.4 237.3 236.8 236.6
Curvy 29.5 29.5 29.5 35.0 34.8 34.7 50.0 50.0 50.0 66.7 66.5 66.5 107.1 106.9 106.9 141.2 140.6 140.6 197.0 197.0 197.0 239.6 239.1 238.9
Very curvy 29.7 29.6 29.6 35.4 35.2 35.2 50.3 50.2 50.2 67.5 67.3 67.3 108.6 108.3 108.3 142.6 142.6 142.6 198.6 198.6 198.6 242.3 242.1 242.1
8 Straight 30.6 30.4 30.4 37.4 37.2 37.2 54.2 54.1 54.1 75.5 75.3 75.3 131.4 131.4 131.4 162.3 162.3 162.3 248.9 248.9 248.9 297.0 296.6 296.6
Curvy 30.7 30.5 30.5 37.7 37.5 37.4 54.4 54.3 54.3 75.8 75.6 75.6 132.0 132.0 132.0 162.3 162.3 162.3 251.5 251.5 251.5 299.3 299.3 298.9
Very curvy 31.0 30.8 30.8 38.0 37.8 37.8 54.7 54.6 54.6 76.3 76.1 76.1 133.1 133.1 133.1 163.3 163.3 163.3 251.3 251.3 251.3 302.0 302.0 302.0
10 Straight 32.5 32.3 32.3 40.6 40.4 40.4 59.5 59.4 59.4 85.8 85.8 85.8 159.5 159.5 159.5 189.0 189.0 189.0 307.7 307.7 307.7 364.5 364.5 364.5
Curvy 32.6 32.5 32.4 40.7 40.6 40.5 59.8 59.7 59.7 85.9 85.9 85.9 159.8 159.8 159.8 189.0 189.0 189.0 307.2 307.2 307.2 367.4 367.4 367.4
Very curvy 32.9 32.7 32.7 41.0 40.8 40.8 60.2 60.1 60.1 86.1 86.1 86.1 160.4 160.4 160.4 189.0 189.0 189.0 306.4 306.4 306.4 370.6 370.6 370.1

Roughness = 2 IRI

Vehicle loading = 75% of vehicle payload

Source: ARRB Group Ltd.

Table 30: Fuel consumption (litres per 100 km) for rural (uninterrupted/free flow speed) roads (NIMPAC model speeds)
% GradientCurvatureMedium carRigid trucks
 LCV
(2 axle 4 tyre)  
Light truck
(2 axle 6 tyre)  
Medium truck
(2 axle 6 tyre)
Heavy truck
(3 axles)
Large bus
(3 axles)
Articulated truck
(6 axle)
B-Double
(9 axles)
Road widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad width
4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m
Flat Straight 9.1 10.7 11.1 8.8 9.9 10.3 12.2 13.5 14.4 20.1 22.6 23.7 35.1 39.5 41.6 30.5 34.2 35.9 56.0 62.7 65.8 67.4 75.5 82.1
Curvy 8.8 9.6 9.8 8.6 9.1 9.2 11.2 11.9 12.3 19.1 20.6 21.0 33.0 35.5 36.2 28.5 29.3 29.8 50.2 51.6 52.0 65.6 70.3 72.8
Very curvy 8.7 9.0 9.0 8.7 9.0 9.0 10.8 11.2 11.3 20.0 20.9 21.5 34.5 35.8 36.3 29.3 29.6 29.6 49.7 50.3 50.3 70.3 72.9 74.7
4 Straight 9.2 10.6 10.9 9.3 10.0 10.1 12.2 13.0 13.6 22.5 23.1 23.4 44.6 44.8 45.0 41.6 41.4 41.3 74.2 74.1 74.0 105.3 106.2 106.9
Curvy 9.0 9.7 9.8 9.2 9.5 9.5 11.5 11.9 12.1 22.2 22.5 22.6 44.5 44.6 44.6 42.0 41.8 41.8 75.1 75.0 75.0 105.4 106.0 106.3
Very curvy 8.8 9.1 9.1 9.4 9.5 9.5 11.2 11.4 11.5 22.5 22.8 22.8 45.1 45.2 45.2 42.7 42.6 42.6 76.1 76.0 76.0 106.6 107.0 107.3
6 Straight 9.2 9.8 9.9 10.6 10.6 10.6 13.1 13.3 13.4 27.5 27.6 27.6 58.0 57.9 57.9 55.3 55.1 55.1 102.4 102.0 102.0 141.4 141.6 141.7
Curvy 9.1 9.5 9.5 10.6 10.6 10.6 12.9 13.0 13.1 27.4 27.5 27.6 58.1 58.0 58.0 55.5 55.3 55.3 102.4 102.4 102.4 142.1 142.4 142.5
Very curvy 9.1 9.3 9.3 10.9 10.8 10.8 12.9 13.0 13.0 27.7 27.8 27.8 58.6 58.6 58.6 55.9 55.9 55.9 102.8 102.8 102.8 143.7 143.9 143.9
8 Straight 9.7 9.8 9.8 12.4 12.3 12.3 15.0 15.0 15.0 33.5 33.5 33.5 72.6 72.6 72.6 69.3 69.3 69.3 132.4 132.4 132.4 180.2 180.2 180.2
Curvy 9.7 9.7 9.7 12.5 12.4 12.4 15.0 15.0 15.0 33.6 33.6 33.6 72.8 72.8 72.8 69.3 69.3 69.3 133.4 133.4 133.4 180.9 180.9 181.0
Very curvy 9.7 9.8 9.8 12.7 12.6 12.6 15.2 15.1 15.1 33.7 33.7 33.7 73.1 73.1 73.1 69.6 69.6 69.6 133.6 133.6 133.6 182.0 182.0 182.0
10 Straight 10.7 10.7 10.7 14.5 14.4 14.4 17.5 17.4 17.4 40.0 40.0 40.0 88.0 88.0 88.0 84.7 84.7 84.7 164.1 164.1 164.1 220.9 220.9 220.9
Curvy 10.8 10.7 10.7 14.5 14.5 14.4 17.5 17.5 17.5 40.0 40.0 40.0 88.0 88.0 88.0 84.7 84.7 84.7 164.3 164.3 164.3 221.5 221.5 221.5
Very curvy 10.9 10.8 10.8 14.7 14.6 14.6 17.6 17.6 17.6 40.1 40.1 40.1 88.1 88.1 88.1 84.7 84.7 84.7 164.6 164.6 164.6 222.2 222.2 222.4

Roughness = 2 IRI

Vehicle loading = 75% of vehicle payload

Source: ARRB Group Ltd.

Table 31: Free speed (km/h) tables for rural (uninterrupted/free flow speed) roads (HDM speeds)
% GradientCurvatureMedium carRigid trucks
 LCV
(2 axle 4 tyre)  
Light truck
(2 axle 6 tyre)  
Medium truck
(2 axle 6 tyre)
Heavy truck
(3 axles)
Large bus
(3 axles)
Articulated truck
(6 axle)
B-Double
(9 axles)
Road widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad width
4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m
Flat Straight 97 108 112 104 104 104 83 87 87 82 91 100 70 80 89 71 81 92 82 91 97 82 90 96
Curvy 93 100 102 98 98 98 79 82 82 79 85 91 70 78 84 70 79 86 75 78 79 75 78 79
Very curvy 80 82 82 81 81 81 71 72 73 72 75 77 66 69 71 66 70 71 62 62 62 62 62 62
4 Straight 95 104 107 93 93 93 73 75 75 72 76 81 58 61 64 63 67 71 56 59 60 49 51 53
Curvy 91 97 99 89 89 89 70 72 72 71 74 77 57 60 62 63 66 69 55 55 56 48 48 48
Very curvy 79 81 81 78 78 78 65 66 66 66 68 69 56 57 58 61 62 63 51 51 51 45 45 45
6 Straight 93 100 103 84 84 84 65 67 67 63 66 68 48 50 52 53 56 58 45 47 48 38 40 40
Curvy 90 95 96 81 81 81 63 64 65 62 64 66 48 50 51 53 55 57 44 45 45 38 38 38
Very curvy 79 80 81 73 73 73 60 60 60 59 61 61 47 48 48 52 53 53 42 42 42 36 36 36
8 Straight 89 95 98 75 75 75 58 59 59 55 58 60 41 42 44 45 47 49 38 39 40 31 32 33
Curvy 87 91 92 73 73 73 57 57 57 55 56 58 41 42 43 45 47 48 37 37 37 31 31 31
Very curvy 77 79 79 67 67 67 54 54 54 53 54 54 40 41 41 44 45 46 35 35 35 30 30 30
10 Straight 85 90 92 67 67 67 54 55 56 49 51 53 35 36 37 40 41 42 32 33 34 27 27 28
Curvy 83 87 88 66 66 66 52 53 53 48 50 51 35 36 37 39 41 42 32 32 32 26 26 26
Very curvy 75 76 77 61 61 61 49 50 50 47 47 48 35 35 35 39 39 40 30 30 30 25 25 25

Roughness = 2 IRI

Vehicle loading = 75% of vehicle payload

Source: ARRB Group Ltd.

Table 32: Vehicle operating cost (cents per km) for rural (uninterrupted/free flow speed) roads, June $2013 (HDM speeds)
% GradientCurvatureMedium carRigid trucks
 LCV
(2 axle 4 tyre)  
Light truck
(2 axle 6 tyre)  
Medium truck
(2 axle 6 tyre)
Heavy truck
(3 axles)
Large bus
(3 axles)
Articulated truck
(6 axle)
B-Double
(9 axles)
Road widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad width
4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m
Flat Straight 29.6 30.5 30.9 34.9 34.9 34.9 48.2 48.8 48.9 55.7 57.1 58.9 69.5 71.8 74.9 102.1 102.8 104.4 116.6 120.7 124.0 138.0 141.9 145.0
Curvy 29.5 30.0 30.2 34.6 34.6 34.6 47.8 48.1 48.2 56.0 57.2 58.5 70.1 72.5 75.0 102.8 103.8 105.2 116.0 117.2 117.7 138.1 139.5 140.0
Very curvy 29.4 29.4 29.5 34.2 34.2 34.2 47.4 47.6 47.7 58.2 59.2 59.8 73.5 75.4 76.3 106.7 107.9 108.5 117.6 117.8 117.8 141.9 142.1 142.2
4 Straight 29.8 30.4 30.7 34.5 34.5 34.5 48.3 48.7 48.8 59.4 59.1 59.0 88.4 87.4 86.6 119.3 118.1 117.2 148.7 147.7 147.0 193.1 191.8 190.7
Curvy 29.7 30.1 30.2 34.4 34.4 34.4 48.1 48.3 48.3 59.6 59.4 59.2 88.5 87.6 87.1 119.5 118.5 117.8 149.6 149.2 149.1 194.1 193.7 193.6
Very curvy 29.6 29.7 29.7 34.5 34.5 34.5 48.1 48.2 48.2 60.7 60.7 60.6 89.5 89.1 88.9 121.1 120.6 120.4 152.0 152.0 152.0 196.5 196.4 196.4
6 Straight 30.0 30.5 30.7 34.9 34.9 34.9 50.3 50.2 50.2 66.6 66.2 65.9 109.1 108.0 106.8 136.6 135.3 134.2 186.8 185.3 184.0 250.0 248.4 246.9
Curvy 30.0 30.3 30.4 34.9 34.9 34.9 50.5 50.4 50.4 66.8 66.5 66.3 109.2 108.2 107.4 136.7 135.6 134.9 187.9 187.5 187.3 251.1 250.7 250.5
Very curvy 30.0 30.1 30.1 35.5 35.5 35.5 50.9 50.8 50.8 67.6 67.4 67.3 109.8 109.4 109.2 137.5 137.0 136.8 190.2 190.2 190.2 253.6 253.5 253.5
8 Straight 30.5 30.8 30.9 36.9 36.9 36.9 54.4 54.3 54.2 74.8 74.2 73.6 133.4 132.1 130.7 156.0 154.7 153.5 230.5 228.7 226.9 311.2 309.3 307.5
Curvy 30.5 30.7 30.7 37.1 37.1 37.1 54.6 54.5 54.5 74.9 74.5 74.2 133.5 132.4 131.5 156.1 155.0 154.2 231.7 231.2 231.0 312.5 312.0 311.8
Very curvy 30.6 30.7 30.7 37.7 37.7 37.7 55.1 55.0 55.0 75.5 75.3 75.2 134.1 133.6 133.4 156.8 156.3 156.1 234.3 234.2 234.2 315.3 315.2 315.2
10 Straight 31.5 31.3 31.4 39.5 39.5 39.5 58.7 58.2 58.1 83.8 83.2 82.5 160.2 158.7 157.1 177.2 175.8 174.5 277.2 275.1 273.0 380.7 378.5 376.3
Curvy 31.6 31.5 31.5 39.6 39.6 39.6 59.2 59.0 58.9 83.9 83.5 83.1 160.3 159.0 157.9 177.3 176.1 175.2 278.7 278.1 277.9 382.2 381.7 381.4
Very curvy 32.0 32.0 32.0 40.1 40.1 40.1 60.0 59.9 59.8 84.5 84.3 84.1 160.9 160.4 160.1 177.9 177.4 177.1 281.5 281.4 281.4 385.2 385.2 385.1

Roughness = 2 IRI

Vehicle loading = 75% of vehicle payload

Source: ARRB Group Ltd.

Table 33: Fuel consumption (litres per 100 km) for rural (uninterrupted/free flow speed) roads (HDM speeds)
% GradientCurvatureMedium carRigid trucks
 LCV
(2 axle 4 tyre)  
Light truck
(2 axle 6 tyre)  
Medium truck
(2 axle 6 tyre)
Heavy truck
(3 axles)
Large bus
(3 axles)
Articulated truck
(6 axle)
B-Double
(9 axles)
Road widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad widthRoad width
4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m4.5m5.8m8.5m
Flat Straight 10.0 10.9 11.4 11.1 11.1 11.1 12.6 13.1 13.2 19.7 21.5 23.7 30.9 33.7 37.2 27.2 29.2 31.9 52.7 57.3 61.0 64.8 69.5 73.1
Curvy 9.8 10.4 10.6 10.8 10.8 10.8 12.2 12.5 12.6 19.8 21.4 22.9 31.4 34.3 37.2 27.8 30.0 32.2 51.3 52.9 53.4 64.2 65.9 66.6
Very curvy 9.3 9.4 9.5 10.2 10.2 10.2 11.8 12.0 12.1 21.6 22.8 23.6 34.6 36.8 37.9 31.1 32.9 33.8 51.2 51.5 51.6 65.9 66.2 66.3
4 Straight 10.0 10.7 11.1 10.5 10.5 10.5 11.9 12.3 12.4 22.0 22.0 22.2 44.3 43.9 43.6 41.0 40.7 40.4 73.8 73.5 73.3 103.0 102.7 102.5
Curvy 9.8 10.3 10.5 10.3 10.3 10.3 11.5 11.8 11.8 22.0 22.1 22.1 44.3 44.0 43.8 41.2 40.9 40.7 74.0 73.9 73.9 103.3 103.2 103.1
Very curvy 9.4 9.5 9.6 10.1 10.1 10.1 11.4 11.5 11.5 22.8 22.9 23.0 45.1 44.9 44.9 42.3 42.3 42.3 75.1 75.1 75.1 104.1 104.1 104.1
6 Straight 10.0 10.6 10.9 10.4 10.5 10.5 12.6 12.5 12.5 27.5 27.5 27.4 58.0 57.6 57.3 53.5 53.1 52.8 98.9 98.6 98.3 140.7 140.4 140.1
Curvy 9.9 10.3 10.4 10.4 10.4 10.4 12.6 12.6 12.6 27.6 27.5 27.5 58.0 57.7 57.5 53.5 53.2 53.0 99.1 99.0 99.0 140.9 140.8 140.8
Very curvy 9.6 9.7 9.8 10.8 10.8 10.8 12.8 12.8 12.8 28.0 28.0 28.0 58.3 58.1 58.1 54.0 53.9 53.8 99.8 99.8 99.8 141.5 141.5 141.5
8 Straight 10.2 10.6 10.8 11.9 11.9 11.9 14.8 14.7 14.7 33.5 33.4 33.3 72.5 72.1 71.8 66.7 66.3 66.0 124.9 124.6 124.3 180.6 180.3 180.0
Curvy 10.1 10.4 10.5 12.0 12.0 12.0 14.8 14.8 14.8 33.5 33.4 33.4 72.5 72.2 71.9 66.7 66.4 66.1 125.1 125.0 125.0 180.8 180.7 180.7
Very curvy 9.9 10.0 10.0 12.3 12.3 12.3 15.0 15.0 15.0 33.7 33.7 33.7 72.7 72.5 72.4 66.9 66.8 66.7 125.7 125.7 125.7 181.4 181.4 181.4
10 Straight 10.8 10.8 10.9 13.7 13.7 13.7 17.0 17.0 16.9 39.6 39.5 39.4 87.2 86.8 86.5 80.1 79.7 79.4 152.0 151.7 151.5 222.0 221.7 221.5
Curvy 10.9 10.9 10.8 13.7 13.7 13.7 17.1 17.1 17.1 39.7 39.6 39.5 87.2 86.9 86.7 80.1 79.8 79.6 152.3 152.2 152.1 222.3 222.2 222.2
Very curvy 11.0 11.0 11.0 14.0 14.0 14.0 17.3 17.2 17.2 39.8 39.8 39.7 87.4 87.2 87.2 80.3 80.2 80.1 152.9 152.9 152.8 222.9 222.9 222.9

Roughness = 2 IRI

Vehicle loading = 75% of vehicle payload

Source: ARRB Group Ltd.

5.4 Interrupted flow VOC models

5.4.1 Basis of interrupted flow VOC models

The approach adopted for interrupted flow VOC models was similar to that used for uninterrupted flow. This involved the development of a suite of models for application to interrupted flow conditions, as experienced on urban and sub-urban arterials and freeways depending on variables such as time of day, traffic capacity and intersection types. However, the scope of operating conditions was considered to be more limited although the underpinning basis and potential were the same.

The model development has involved the reconstruction of the models reported by Cox and Arup (1996) and in Austroads (2004), with a simplified vehicle operating cost model and fuel consumption model produced for typical operating conditions, and for a 20 vehicle fleet.

The development of the models adapted the outputs from the uninterrupted flow analysis by modifying the estimates for the different VOC component, as follows:

  • Fuel and lubricating oil consumption, through application of a multiplication factor based on average travel speed
    • Cars and light commercial vehicles
      FF&LCL = 1.9*(1 – 0.004*Speed)
    • Medium and heavy commercial vehicles and buses
      FF&LHV = 2.5*(1 – 0.004*Speed)
  • Repairs and maintenance costs, and tyre consumption, through application of a multiplication factor which varies by vehicle type (Table 5.11), with the full factor applied at 30 km/h and a greater or lesser factor applied at lower and higher speeds with zero additional effect (factor of 1) at a user defined upper value (selected as 100 km/h)
  • Capital and interest, by accounting for reduced utilisation in lower journey speed environments and therefore higher per km costs through application of a multiplication factor
    • FC&I = 60/Speed (in km/h).
Table 34: Multiplication factor for maintenance labour and spare parts and tyre consumption estimates under interrupted flow
Vehicle typeFactor
Cars and light commercial vehicles 1.25
Rigid trucks 1.4
Articulated trucks and buses 1.6

5.4.2 Model structure and coefficients

The form of the interrupted flow VOC models as in Austroads (2004) are as follows:

Stop-start model: c = A + B / V

Free-flow model: c = C 0 + C 1 V + C 2 V 2

where:

A, B, C0, C1, C2 = model coefficients

c = Vehicle operating cost (cents/km)

V = Average travel speed in km/h.

As was the case of Austroads (2004), the stop-start model can be used for estimating the VOC on urban and sub-urban arterial roads, or freeways, at average journey speeds of < 60 km/h, while the free-flow model is aimed at estimating VOC where average journey speeds are > 60 km/h. The choice to switch from between models should be based on the judgement of the user, taking account of such factors as the level of vehicle interaction, evidence of significant speed-change cycles, and stop-start operation.

The VOC coefficients for the models have been re-estimated using 2013 unit values by adapting the outputs from the uninterrupted flow models as described earlier. In this case, however. a single set of operating conditions in terms of road geometry, road width and gross vehicle mass were considered and applied for all 20 vehicles[4]. The resulting coefficients are presented in Table 5.12.

Table 35: VOC model coefficients for stop-start and free-flow models (cents per km), $2013
Vehicle typeStop-startFree-flow
 ABC0C1C2
01. Small Car 12.5242 838.2969 25.7952 -0.1253 0.0010
02. Medium Car 12.6514 1315.5178 35.0470 -0.1751 0.0012
03. Large Car 14.4297 1838.4754 46.1765 -0.2221 0.0014
04. Courier Van-Utility 15.9354 1357.1233 38.4920 -0.1840 0.0014
05. 4WD Mid Size Petrol 21.0481 1328.7944 40.5580 -0.1540 0.0013
06. Light Rigid 33.9697 1543.5546 51.5092 -0.2481 0.0025
07. Medium Rigid 35.8038 2259.9048 62.6793 -0.3002 0.0026
08. Heavy Rigid 57.1600 2556.0769 82.2900 -0.5525 0.0053
09. Heavy Bus 64.5569 4632.1535 124.7014 -0.6467 0.0047
10. Artic 4 Axle 84.5711 3323.0102 111.6621 -0.7240 0.0072
11. Artic 5 Axle 91.1303 3688.6095 119.8994 -0.6800 0.0066
12. Artic 6 Axle 98.6903 3991.2764 128.6879 -0.6878 0.0066
13. Rigid + 5 Axle Dog 122.5511 3729.8458 136.1620 -0.6403 0.0065
14. B-Double 122.9920 4592.1836 151.4716 -0.7228 0.0068
15. Twin steer + 5 Axle Dog 127.1973 4379.9716 149.9310 -0.6911 0.0067
16. A-Double 143.9930 5692.0036 183.5354 -0.8330 0.0074
17. B Triple 149.4138 7134.4573 214.1429 -0.9878 0.0081
18. A B Combination 170.3213 6257.8473 208.7075 -0.9017 0.0080
19. A-Triple 190.6482 7134.9278 237.0682 -1.0131 0.0086
20. Double B-Double 199.5704 6976.3148 238.7248 -0.9882 0.0086

The fuel consumption coefficients for the same range of conditions are presented in Table 5.13.

Table 36: Fuel consumption coefficients for coefficients for stop-start and free-flow models, (litres per 100km) $2013
Vehicle typeStop-startFree-flow
ABC0C1C2
01. Small Car 7.9302 117.1284 7.9340 -0.0636 0.0007
02. Medium Car 8.8017 179.6890 9.8014 -0.0785 0.0008
03. Large Car 10.4870 255.0092 12.3217 -0.0914 0.0009
04. Courier Van-Utility 8.0758 226.1850 10.8957 -0.1125 0.0011
05. 4WD Mid Size Petrol 11.5401 246.2530 12.4016 -0.0832 0.0009
06. Light Rigid 16.0634 147.3128 10.8435 -0.1123 0.0016
07. Medium Rigid 28.5369 158.8351 16.3326 -0.1075 0.0018
08. Heavy Rigid 45.5089 535.1584 32.0378 -0.2949 0.0040
09. Heavy Bus 38.3297 661.0688 30.2018 -0.2507 0.0029
10. Artic 4 Axle 63.9608 458.9412 40.1353 -0.3541 0.0053
11. Artic 5 Axle 68.7011 507.3099 42.3944 -0.3260 0.0049
12. Artic 6 Axle 75.4028 547.8857 45.8457 -0.3168 0.0049
13. Rigid + 5 Axle Dog 90.1180 616.4443 53.6148 -0.3176 0.0050
14. B-Double 96.3563 651.9121 56.8966 -0.3128 0.0050
15. TS + 5 Axle Dog 96.5790 659.1193 57.0718 -0.3104 0.0050
16. A-Double 112.0411 723.6597 65.1119 -0.3119 0.0051
17. B Triple 117.0878 745.8925 67.7203 -0.3110 0.0052
18. A B Combination 131.0548 798.2622 74.8085 -0.3105 0.0053
19. A-Triple 145.7190 855.7539 82.2758 -0.3084 0.0055
20. Double B-Double 150.8098 877.3157 84.8826 -0.3070 0.0055

[1] Practitioners are therefore able to use the payloads as inputs to the VOC models described in the rest of this section, with corresponding ESAs for their analysis. This provides a link for practitioners between VOCs, which can be estimated using these models, and vehicle loading, which also has an effect on road pavement, especially as loads increase. For sealed granular pavements, the most common type in Australia, this is based on a simple model where the relative damage (in ESA or Standard Axle Repetitions) = (Axle load/Standard load)4, hence the commonly used term ‘4th power law’. For example, a standard load of 80kN and an actual load of 100kN, the relative damage for an increase in total load of 25% is approximately (100/80)4 or 2.45 times the effect of a standard load. For further guidance, reference should be made to the Guide to Pavement Technology Part 2: Pavement Structural Design (Austroads, 2012d) and specialist advice sought in its application.

[2] Passenger car units (PCUs) and passenger car space equivalents (PCSEs) held to be the same for all traffic conditions.

[3] Roughness in Australia is generally held to not exceed IRI of 6, so extreme roughness is held to not be a major issue, hence the focus on 1.2-5.8 IRI for Australia in Austroads (2012b).

[4] The extension of the number of vehicle categories from the limited number in Austroads (2004) to the 20 vehicle classification in the ATAP highlights the importance of what is assumed to be a representative vehicle in a particular category where a limited number of vehicle types is used. These differences are reflected in the coefficients in the model over time.