International Journal of Scientific & Engineering Research, Volume 4, Issue 9, September-2013 1464

ISSN 2229-5518

Calibrating Road User Cost Model in HDM-4 for Conditions Prevailing in India – A Case Study

Aswathy Das A, Dr. Bino I Koshy, Jeena Pradeep

Abstract—Engineering economic analysis applies economic concepts and methods to engineering problems to support decisions on a best course of action. Economic analysis provides a way of comparing the economic gains expected from an investment with the cost of that investment; providing an objective understanding of value to be expected for cost incurred. The Highway Development and Management Model (HDM-4) system is seen as the international standard decision support tool for road management. This article focuses on the Road User Cost Modelling in HDM-4 and validation of the model using Road User Costs Knowledge System (RUCKS).

Index Terms— Road User Costs, Vehicle Operating Cost, Travel Time Cost, HDM-4, RUCKS.

—————————— ——————————


HE economic analysis is a critical component of a com- prehensive project or program evaluation methodology that considers all key quantitative and qualitative impacts
of highway investments. It allows highway agencies to identi- fy, quantify, and value the economic benefits and costs of highway projects and programs over a multiyear timeframe. With this information, highway agencies are better able to tar- get scarce resources to their best uses in terms of maximizing benefits to the public and to account for their decisions.


The objective of the cost benefit analysis is to identify and quantify the benefits and costs associated with the project. This analysis will help in identification of the optimum solu- tion along with the economic viability in terms of its likely investment return potential.

2.1 Cost Components in Transportation System

In broad terms, the society costs pertaining to the highway development, to be considered in this analysis includes:
Agency costs: Capital cost, Recurrent cost for maintenance (an- nual & periodical), Residual value at the end of analysis peri- od
Road user costs: Vehicle operating cost, Travel time cost, Acci- dent cost

2.2 Benefit Component in Transportation System

The objective of a good transportation system is to provide an efficient, quick and safe transportation to its users. And this is counted as the benefit of transportation. The various possible


Aswathy Das A is currently pursuing Masters degree in Transportation Engineering from Rajiv Gandhi Institute of Technology, Kottayam, Kerala E-mail: /

Dr Bino I Koshy is currently working as Professor, Department of Civil

Engineering, Rajiv Gandhi Institute of Technology, Kottayam, Kerala

Jeena Pradeep is currently working as General Manager(Transport Plan-

ning), CDM Smith India Pvt. Ltd., Bangalore

forms of benefits can be summarized as follows (IRC: SP-30,


Road user benefits: This type of benefit includes, saving in VOC,

saving of travel time, saving in terms of accident cost, saving
in the cost of maintenance etc.

Social benefits: This type of benefit includes, benefit due to im-

provement in administration, health, education, agriculture,
industry, trade, environmental standards etc.


Selecting the optimal alternative in transportation projects can be a very complex affair. Thus with new developments in technology, computer models and programs were used for the economic analysis so that the complex task of analysis be- comes much easier. There are a number of softwares available for the economic analysis of road projects including Micro- BENCOST, Cal B/C, Redbook Wizard, RED, HDM-III, HDM-4 etc. HDM-4 is one among the best software’s available for eco- nomic analysis being developed by World Bank and accepted worldwide. Primary and secondary data needed as inputs to these softwares are huge.


The Highway Design and Maintenance Standards Model (HDM-III) is a computer program for analyzing the total transport costs of alternative road improvement and mainte- nance strategies through life-cycle economic evaluation. The program provides detailed modeling of pavement deteriora- tion and maintenance effects, and calculates the annual costs of road construction, maintenance, vehicle operation, and travel time needed to perform the economic evaluation of the alternatives being considered.

3.2 HDM-4

The Highway Development and Management Model (HDM-4) Version 1.3 was released in January 2002 which is the recom- mended software for evaluating highway investment options. HDM-4 is the result of the International Study of Highway

IJSER © 2013

International Journal of Scientific & Engineering Research, Volume 4, Issue 9, September-2013 1465

ISSN 2229-5518

Development and Management (ISOHDM) that was carried out to extend the scope of the World Bank’s HDM-III model. The system has become the de-facto standard for road invest- ment analysis for many road authorities and financing agen- cies.


As part of the International Study of Highway Development and Management Tools (ISOHDM), a compendium was com- piled of the countries where HDM had been applied. HDM or its relationships has been applied in over 100 developed and developing countries having markedly different technological, climatic and economic environments. Since the model simu- lates future changes to the road system from current condi- tions, the reliability of the results is dependent upon two pri- mary considerations:
• How well the data provided to the model represent the reality of current conditions and influencing fac- tors, in the terms understood by the model; and,
• How well the predictions of the model fit the real be- haviour and the interactions between various factors for the variety of conditions to which it is applied.
Thus before analysis, the system will have to be calibrated to the existing conditions or the prevailing conditions of the study area or country [2].


The project stretch being selected for the present study is a part of an important State Highway of Kerala. The project stretch has a length of about 47km and average carriage way width of 7.5 m. A huge number of inputs are needed for anal- ysis in software. Data collection includes primary data and secondary data.

5.1 Primary data

Primary data includes the classified volume count survey, road side interview survey, and pavement condition survey was collected for the project stretch.

5.2 Secondary data

The inputs needed in HDM-4 are enormous and for each rep- resentative vehicle the basic data like the following were col- lected from secondary sources and calculations:

Basic characteristics

• Physical: Passenger car space equivalent, number of
wheels, number of axles
• Tyres: Tyre type, base number of recaps, retread cost
• Utilization: Annual km, working hrs, average life,
private use, passengers, work-
related trips
• Loading: Equivalent Single Axle Load Factor(per ve-
hicle), operating weight

Economic unit costs

• Vehicle resources: new vehicle, replacement tyre, fuel,
lubricating oil, maintenance labour,
crew wages, annual overhead, annual interest
• Time value: passenger working time, passenger non-
working time, cargo.
Table 1represents the calculation of time value from NSDP
(Net State Domestic Product).




*Full-time equivalent workers, assuming marginal workers are employed half-time
**Assuming 2,400 worked hours per year
From the time value of bus passenger the time value of mini bus, two wheelers, car and autorickshaw was calculated. Table 2 gives the values arrived at for the other vehicle types.



Vehicle Type

Time value (Rs / Hour)


Non work




Mini Bus (= Bus*1.20)



Two Wheeler (= Bus *1.40)



Car (= Bus *1.75)



Auto Rickshaw (= Car*0.70)



5.3 Analysis of primary data

Table 3 gives an idea of the results that are obtained from the analysis of survey data using Microsoft Excel applications.

IJSER © 2013

International Journal of Scientific & Engineering Research, Volume 4, Issue 9, September-2013 1466

ISSN 2229-5518



Sl. No


Results from analysis of survey data


Classified Vol- ume Counts

(3 days-24 hrs)

1. Average Daily Traffic


2. Daily variation of traffic

3. Peak Hour Traffic

4. Directional Distribu-


5. Annual Average Daily

Traffic (AADT)


Origin Destina- tion & Commod- ity Survey

(1 day- 24hrs)

1. Zone wise influence

2. Trip Distribution

3. Trip frequency distribu-


4. Commodity Distribution

5. Trip Purpose Distribution

6. Trip length distribution


Axle load sur-


(1 day- 24hrs)

1. Equivalent Single Axle

Load (ESAL)

2. Vehicle Damage Factor


Pavement Condi-

tion Survey

1. Distresses (in %)

2. Pavement Condition

3. Shoulder Condition

4. Road Side Drain

5. Right of way(m)

6. Carriage Way


It is important that prior of using HDM-4 for the first time in any country, the system should be configured and calibrated for local use. Since HDM-4 has designed to be used in a wide range of environments, calibration of HDM-4 provides the facility to cus- tomize system operation to reflect the norms that are customary in the environment under study (Bennett et al).
Calibration of the HDM model focuses on the two primary components which determine the physical quantities, costs and benefits predicted for the analysis, namely:
• Road User Effects (RUE) ; and
• Road Deterioration and Maintenance Effects (RDME)
The degree of local calibration appropriate for HDM is a
choice that depends very much on the type of application and on the resources available to the user. For example, in planning ap- plications the absolute magnitude of the RUE and road construc- tion costs need to match local costs closely because alternative
capital projects with different traffic capacities or route lengths are evaluated on the comparison of the total road transport costs. In road maintenance programming, on the other hand, the sensi- tivity of RUE to road conditions, particularly roughness, and all the road deterioration and maintenance predictions are the most important aspects [2].

6.1 Levels of Calibration

There are three levels of calibration for HDM, which involve

low, moderate and major levels of effort and resources, as


Level 1 - Basic Application

This level determines the values of required basic input pa-
rameters, adopts many default values, and calibrates the most
sensitive parameters with best estimates, desk studies or min-
imal field surveys.

Level 2 - Calibration

This level requires measurement of additional input parame-
ters and moderate field surveys to calibrate key predictive
relationships to local conditions. This level may entail slight
modification of the model source code.

Level 3 - Adaptation

This level undertakes major field surveys and controlled ex-
periments to enhance the existing predictive relationships or
to develop new and locally specific relationships for substitu-
tion in the source code of the model.

6.2 Road User Effects (RUE)

Road user effects (RUE) comprise of vehicle operating costs (VOC), travel time, accident costs, vehicle emissions (noxious gases and noise), and developmental effects. The use of ap- propriate calibration factors in HDM-4 pavement deterioration models will facilitate more reliable and rational prediction of pavement deterioration for the road network under considera- tions [2].

6.3 Road Deterioration and Maintenance Effects


Road Deterioration and Maintenance Effects (RDME) are comprised of the deterioration of the pavement and the impact of maintenance activities on pavement condition and the fu- ture rate of pavement deterioration [2].
In this study focus is on Road User Effects (RUE) calibra- tion rather than the Road Deterioration and Maintenance Ef- fects (RDME). Hence the calibration factors of HDM-4 pave- ment deterioration models derived for Indian conditions by Aggarwal et al (2005) are being used.


After the calibration of HDM-4 to the local conditions, the model will have to be validated. For this purpose, Road User Costs Knowledge System (RUCKS) released by World Bank on February 18, 2010 is being used.
As mentioned earlier Vehicle Operating Cost (VOC) is an important component of the Road User Cost (RUC) and also it consists of more number of variables like economic costs of fuel, lubricants, tyre, maintenance parts, maintenance labor, crew time, depreciation, interest, overhead etc rather than travel time cost and accident cost components in Road User Cost. So for the process of validation, Vehicle Operating Cost values from both the applications are compared.
For the purpose of running the analysis in HDM-4 at least two alternatives including the base case should be considered. Thus two scenarios are considered including the present con- dition for the study:
• Base option or ‘do-nothing’ which is the present con- dition of the project stretch i.e., in 2013

IJSER © 2013

International Journal of Scientific & Engineering Research, Volume 4, Issue 9, September-2013 1467

ISSN 2229-5518

• Four laning of the existing two lane road or ‘do- something’ which is the expected condition of the project stretch in 2017 after the four laning works are completed and the facility is open to public
Ten vehicle types were used for the validation of the calibrat- ed RUC model of HDM-4 using RUCKS. The result of VOC obtained is as represented in Table 4.


er Cost was found. As a thumb rule the percentage of Travel Time Cost (TTC) should be more for passenger vehicles i.e.; in the range of 70% or more and Vehicle Operating Cost (VOC) around 30% or below. While for commercial vehicles this TTC component should be below 5% and VOC should be above
95%. Table 5 shows the percentage for each vehicle type.





Vehicle Type



3-axle trucks 97% 3% 97% 3% Auto Rickshaws 40% 60% 42% 58% Bus 30% 70% 42% 58% LCV+Mini LCV 97% 3% 98% 2% Mini Bus 29% 71% 30% 70% Multi-axle 97% 3% 97% 3% New Tech Car 29% 71% 29% 71%

Old Tech Car 46% 54% 46% 54%
Tempo or Mini

98% 2% 98% 2%

Two Wheeler 23% 77% 26% 74%


From Table 4 and Figure 1 it is clear that a remarkable dif- ference in VOC is obtained in case of Bus and Mini LCV while other values are acceptable. A variation upto 15% is consid- ered to be acceptable. However the variation in value of 2 ve- hicle types may be because of the difference in vehicle feature in HDM-4 and RUCKS.
Hence it was necessary to check which component shows the variation. For this purpose the percentage of Vehicle Op- erating Cost and Travel Time Cost which comprises Road Us-
From the table above its clear that the percentage of VOC and TTC for bus is not matching with the thumb rule in case of values form RUCKS. But the percentage matches in case of HDM-4 showing a correction needed only for RUCKS. As this project uses HDM-4 there is no need for correction. Thus, the software is being calibrated and can be used for economic analysis


While validating the values obtained in HDM-4 using RUCKS,
8 vehicle types were found to have only very minor variation
in values while 2 vehicle types (Bus, Mini LCV) especially Bus,
was found to have remarkable variation. A variation of value
up to 15% was considered acceptable for the validation. How-
ever the percentage of RUC that goes into VOC for bus is ac-
ceptable in case of HDM-4. Thus the calibration of Road User
Cost in HDM-4 was found to be acceptable. As an extension to
the work, economic analysis of the road improvement scheme
can also be carried out in future.


[1] J Barry Standish. (2010) “An Economic Analysis of the Gauteng Freeway Improvement Scheme”, Graduate School of Business, University of Cape Town, August 2010

[2] Christopher R. Bennett and William D. O. Paterson. (2000) “A Guide to Cali- bration and Adaptation”, Volume-Five, HDM-4 User Guide

[3] Dinh Van Hiep. “HDM-4 Application For Management And Maintenance Of

IJSER © 2013

International Journal of Scientific & Engineering Research, Volume 4, Issue 9, September-2013 1468

ISSN 2229-5518

Road Networks In Vietnam: Pitfalls & Future Directions”, Lecture for Road

Infrastructure Asset Management Course, Kyoto University & UTC Joint

[4] Eric Thompson, David Rosenbaum and Arthur Hall. (2008) “Evaluating Roads as Investments: A Primer on Benefit-Cost and Economic-Impact Anal- ysis”, Technical Report 08-0425, The Center for Applied Economics

[5] H R Kerali, R Robinson and W D O Paterson. (1998) “Role of the New HDM-4 in Highway Management”, 4th International Conference on Managing Pavements

[6] H.R. Kerali, J.B. Odoki, D.C. Wightman and E.E. Stannard. (1998) “Structure of the new Highway Development and Management Tools (HDM-4)”, 4th International Conference on Managing Pavements

[7] IRC: SP-30. (1993) “Economic Evaluation of Highway Projects in India”, Indi- an Road Congress

[8] Ishtiaque Ahmed. (2009) “Project Appraisal-Cost-Benefit Analysis of

Transport Projects”, World Bank

[9] J Rolt, P Fouracre and A Davis. (2005) “ A guide to road project appraisal”, Overseas Road Note 5, UK Department for International Development, Pub- lished 2005, ISBN: 0-9543339-6-9

[10] James Adu. (2009) “Financing And Evaluation Of Investments In Road Infra- structure Development”, A Thesis Submitted To The Institute Of Distance Learning, Kwame Nkrumah University Of Science And Technology

[11] L.R. Kadiyali, N.B. Lal and Rakesh Sati. (2006) “Cost-Benefit Analysis Of

Rural Roads Incorporating Social Benefits”, L.R. Kadiyali and Associates

[12] Michael Iacono and David Levinson. (2009) “The Economic Impact of Up- grading Roads: Draft Final Report”, University of Minnesota, Department of Civil Engineering, 500 Pillsbury Drive SE, Minneapolis, USA

[13] Michael J. Markow. (2012) “Engineering Economic Analysis Practices for Highway Investment”, A Synthesis of Highway Practice, Transportation Re- search Board Washington, D.C.

[14] Nantarat Tangvitoontham and Papusson Chaiwat. (2012) “Economic Feasibil- ity Evaluation of Government Investment Project by Using Cost Benefit Analysis: A Case Study of Domestic Port (Port A), Laem-Chabang Port, Chonburi Province”, Procedia Economics and Finance

[15] Ningning Zheng, Guoxin Liu and Yee-Chuang Jin. (2010) “Evaluation of Tools for Incorporating Road User Costs in Pavement Rehabilitation Decision Making on Rural Highways in Saskatchewan”, Traffic and Transportation Studies, ASCE 2010

[16] Odoki J B and Henry G. R. Kerali. (2000) “Analytical framework and model descriptions”, Volume-Four, HDM-4 User Guide

[17] P A Pienaar, A T Visser and L Dlamini. (2000) “A Comparison of the HDM-4 with the HDM-III on a case study in Swaziland”, South African Transport Conference ‘Action in Transport for the New Millennium’

[18] Pedro Belli, Jock Anderson, Howard Barnum, John Dixon and Jee-Peng Tan. (1998) “Handbook on economic analysis of investment operations, Chapter-

11”, Operational Core Services Network, Learning and leadership center

[19] Rodrigo Archondo-Callao. (2004) “The Roads Economic Decision Model (RED) for the Economic Evaluation of Low Volume Roads Software User Guide & Case Studies”, Sub-Saharan Africa Transport Policy Program, SSATP Working Paper No. 78

[20] S. S. Jain, Sanjiv Aggarwal, and M. Parida. (2005) “HDM-4 Pavement Deterio- ration Models for Indian National Highway Network”, Journal of Transporta- tion Engineering, ASCE, August 2005

[21] Sanjiv Aggarwal, S.S. Jain and Dr. M. Parida. (2004) “Pavement Management System For A National Highway Network In India”, 6th International Con- ference on Managing Pavements

[22] Yi Jiang, Guangyuan Zhao and Shuo Li. (2010) “Comparison of Software

Packages for Life Cycle Cost and Benefit Analysis of Highway Projects”, Sus- tainable Transportation Systems, ASCE, 2010

IJSER © 2013