Calibration

The Monetised Benefits and Costs Manual (MBCM) includes non-market values to be used in cost–benefit analysis of transport projects. This study conducted a national stated preference survey using face-to-face surveys (n = 7,203) and a choice modelling approach to derive new values to update those in the current manual. Survey questions that asked respondents to choose their preferred road route and/or public transport service option were used to derive values for time for different trip lengths and purposes, and whether sitting or standing on public transport. They also were used to derive values for reliability of travel time and time in congestion. A different set of questions was used to derive values for reductions in fatalities and injuries. The choice questions provided respondents with options for government programmes that differed in cost to them and in total annual numbers of road deaths and injuries. The results suggest the benefit of significant changes to some of the values in the current MBCM, including for the base value of travel time and for the value of preventing a fatality.

Surveying the condition of the pavement is one of the most important processes in managing the road network. The information collected during these surveys allows for the calculation of the Pavement Condition Index, which is a derivative cumulative qualitative indicator that evaluates various pavement characteristics and defects. Deterioration modelling of these measured indicators and calculated indices is a critical element and its most accurate prediction brings the process of pavement management closer to a higher quality process by more efficiently allocating funds and repair work.

Many different models – both extremely complex and simple – are used in the world to simulate the condition of individual pavement indicators. However, these models are developed based on the data of a certain country or region and are not suitable in another country due to different requirements for pavement structures and other reasons. In Lithuania, measurements of the quality indicators of road surfaces with new generation survey equipment have been carried out recently but the information stored in the databases about road sections is minimal, and it becomes difficult to adapt the models applied abroad due to the missing information. The aim of this study is to create pavement condition index prediction models by evaluating such quantitative and qualitative indicators as traffic loads, road surface unevenness, type of repair, pavement age, climatic zones, and pavement construction classes.

India’s growing demand for adequate maintenance and upkeep of the world's second-largest road network of 5.89 million kilometers is a major problem for road administrators and policymakers. To address the issue of proper upkeep of road networks, many countries have implemented a robust pavement management system (PMS) to handle the tasks related to pavement maintenance and management. The Highway Development and Management (HDM-4) system is widely used as a tool for highway investment and maintenance planning and programming. The broad objective of this study is to develop pavement deterioration models for cracking, ravelling, potholes, rut depth, and edge break using non-linear regression techniques in MATLAB and compare them with the models present in HDM-4 and observed deteriorations for their effectiveness. The deterioration models for urban and rural pavement sections have been developed based on the large volume of field data collected in the Jaipur district of Rajasthan State using automated as well as manual methods of field evaluation. These sections were continuously monitored for 5 years for the pavement surface condition data. The validity of these models and calibrated HDM-4 models was assessed by examining the distress predictions generated by the regression models and calibrated deterioration models to the distress observed on the selected pavement sections. The proposed pavement deterioration models and the calibrated HDM-4 models are likely to apply to other developing nations with comparable traffic patterns, soil types, meteorological conditions, terrain kinds, and pavement composition as well.

A dissertation presenting how EVs could be modelled with HDM-4. This shows the potential for major distortion of results as the capital costs are twice those with ICE vehicles.

In this paper the Non-Motorized Traffic (NTM) model of the HDM-4 (Highway Development and Management) is applied for the analysis of different alterna1ves for bicycle lanes, evalua1ng aspects such as current and potenial cyclists demand, operation speed, capital costs and economic profile of bicycle users.

Detailed analysis of the total cost of ownership (TCO) consisting of all costs related to both purchasing and operating the vehicle. This TCO analysis builds on previous work to provide a comprehensive perspective of all relevant vehicle costs of ownership. In this report, we present what we believe to be the most comprehensive explicit financial analysis of the costs that will be incurred by a vehicle owner. This study considers vehicle cost and depreciation, financing, fuel costs, insurance costs, maintenance and repair costs, taxes and fees, and other operational costs to formulate a holistic total cost of ownership and operation of multiple different vehicles. For each of these cost parameters that together constitute a comprehensive TCO, extensive literature review and data analysis were performed to find representative values in order to build a holistic TCO for vehicles of all size classes. The light- and heavy-duty vehicles selected for analysis in this report are representative of those that are on the road today and expected to be available in the future. Table ES-1 summarizes the main parameters in this study, including the cost components which comprise TCO, the sizes and vocations of vehicles which are analyzed, the powertrains of these vehicles, and the model year for analysis of both current and future vehicles.

: The International Roughness Index (IRI) has been accepted globally as an essential indicator for assessing pavement condition. The Laos Road Management System (RMS) utilizes a default Highway Development and Management (HDM-4) IRI prediction model. However, developed IRI values have shown the need to calibrate the IRI prediction model. Data records are not fully available for Laos yet, making it difficult to calibrate IRI for the local conditions. This paper aims to develop an IRI prediction model for the National Road Network (NRN) based on the available Laos RMS database. The Multiple Linear Regression (MLR) analysis technique was applied to develop two new IRI prediction models for Double Bituminous Surface Treatment (DBST) and Asphalt Concrete (AC) pavement sections. The final database consisted of 83 sections with 269 observations over a 1850 km length of DBST NRN and 29 sections with 122 observations over a 718 km length of AC NRN. The proposed models predict IRI as a function of pavement age and Cumulative Equivalent Single-Axle Load (CESAL). The model’s parameter analysis confirmed their significance, and R2 values were 0.89 and 0.84 for DBST and AC models, respectively. It can be concluded that the developed models can serve as a useful tool for engineers maintaining paved NRN.

A techno-economic model is developed based on road-load simulation results expressed in relation to slip energy (SE) at the tire–pavement interface and the repair and maintenance (R&M) cost obtained from published sources and data from state agencies. Tire SE allows for the consideration of aggressive acceleration and deceleration, high torque conditions (for instance, driving an upslope grade), and roadway curvature. Tire SE data used in this effort were generated using physics-based simulation models of different vehicle types for arrays of road conditions (e.g., grades, curvatures) and driving cycles (i.e., vehicle speed profiles). R&M costs were estimated for various vehicle categories and accumulated vehicle mileage. The approach is based on relating the probability density functions (PDFs) of SE and R&M costs. Asymptotic series expansion for an incomplete gamma function was used to approximate the gamma functions and to determine the gamma ratio function that is used as the coefficient to SE to estimate R&M costs. The average R&M cost per mile results from the model compared with the arithmetic mean R&M cost data from fleet operators and published data. The model can serve as a method for predicting R&M cost as a function of road load to vehicle fleet.

Deficiency or inadequate allocation of road maintenance and development funds leads to total road network degradation. In order to ensure proper condition of road pavement with a limited budget, we need road maintenance optimisation for the entire road network. The road maintenance optimisation can be achieved using knowledge-based strategic planning systems. The collection and analysis of necessary data help design different road maintenance long-term strategies. The output results help select priorities for road maintenance and proper fund allocation. Optimal road maintenance strategy is the way to keep a fairly good road network with available funds. In addition, the road user costs can be reduced. The aim of this paper is to offer a road maintenance management system for Lithuanian conditions. The model will help evaluate the performance of the current road network and prepare a multi-year priority list for road works.

Roadway is one of the most crucial transportation modes to cater to inland movement within a country. The agency mandate is to design, construct, and maintain the road to sustain the traffic up to its design life without further strengthening. However, some
factors are affecting the performance of the pavement. Most pavements start to show some traces of deterioration after construction and opening to traffic, but once neglected, the distress portions would be aggravated with corresponding increasing maintenance cost. Thus, the road's maintenance has to be carried out at the place, right schedule, right quality, and at the least cost. Since there are different maintenance alternatives, the best strategy has to be chosen following the road's condition and the severity of the damage. To select the best maintenance alternative, calculations on the pavement layer's property are performed. The Highway Development and Management (HDM-4) tool can do such measures to help decide which option is the best by evaluating the economic and structural conditions. This paper contains two significant areas that are studied. First, it was assessed the procedures followed by the city's road authority to develop the appropriate road maintenance strategies. Questionnaire surveys and interviews are used to collect information from the city's road maintenance departments. Second, the project analysis was performed for structural and economic comparison of different maintenance alternatives using HDM-4. In the analyses, three selected road segments are considered and collected important input data like road condition data, road network data, vehicle fleet data, estimated AADT, and International Roughness Index (IRI). There were five maintenance alternatives have been defined, and proposed maintenance alternatives are compared. The selection is based on the deteriorated pavement, which showed the average roughness for every section of the road network, considering an analysis period of 20 years and cost stream ranking for their Net Present Value and IRR. Results indicated that using a mill and replace, and
routine maintenance schedule for the selected road networks is economically viable and structurally significant. Hence, the city's road authority is recommended to apply the different maintenance strategies, providing an economical and better performance for the city's road network.

Excellent PhD dissertation on developing structural deterioration models for flexible pavements for the Queensland road network using Traffic Speed Deflectometer (TSD) data collected over a five-years period by the Department of Transport and Main Roads (TMR), Queensland. 

TRB Webinar on speed and fuel consumption relationship.

This paper presents an assessment of the accuracy of the HDM-4 fuel consumption model. The study focuses on HGVs and compares estimates made by HDM-4 to measurements from a large fleet of vehicles driving on motorways in England. The data was obtained from the telematic database of truck fleet managers (SAE J1939) and includes three types of HGVs: light, medium and heavy trucks. Some 19,991 records from 1645 trucks are available in total. These represent records of trucks driving at constant speed along part of the M1 and the M18, two motorways in England.

These conditions have been simulated in HDM-4 by computing fuel consumption for each truck type driving at a constant speed of 85 km/h on a flat and straight road segment in good condition.

Estimates are compared to real measurements under two separate sets of assumptions. First, the HDM-4 model calibrated for the UK has been used. Then, the model was updated to take into account vehicle weight and frontal area specific to the considered vehicles.

The paper shows that the current calibration of HDM-4 for the United Kingdom already requires recalibration. The quality of the model estimates can be improved significantly by updating vehicle weight and frontal area in HDM-4. The use of HGV fleet and network condition data as described in this paper provides an opportunity to verify HDM-4 continuously.

The Highway Development and Management model (HDM-4) is a tool developed by the World Bank to aid highway administrators and engineers in the process of decision making for preparing of road investment programme and determining the road network maintenance strategies. HDM-4 essentially models the interaction between the traffic volume, environment and pavement composition to predict the different kinds of distress that develop in pavements over time. Since distress is caused due to different conditions and progresses at different rates, therefore it is necessary to calibrate the HDM-4 model as per the local conditions. The aim of the study is to calibrate the HDM-4 pavement deterioration model in terms of rutting and roughness for the urban road network of Patiala (Punjab, India). In our study, we select 15 road sections and group them based on varying traffic and pavement age. The pavement condition data, which was measured starting from 2012 to the end of 2014, is fed as the input to the HDM-4 distress models. The calibration process is performed using statistical analysis between the observed and predicted value of the distress by keeping minimum Root Mean Square Error (RMSE) and maximum R-squared(R2 ). The determined calibration factors are validated and further used for developing pavement deterioration models which prove to be helpful in building a Pavement Maintenance and Management system for Patiala.

This study aims to calibrate an HDM-4 model to predict pavement deterioration due to structural cracking and ravelling in a selected road section in Patiala (Punjab, India). The steps involved in calibration include modelling the past patterns of pavement deterioration and comparing them with the present-day measurement in order to make adjustments to the model. Data from 15 selected road sections of Patiala was collected for three successive years, starting from the year 2012 to the end of the year 2014, to create the model. Root Mean Square error and Coefficient of Determination were used for evaluating the deviation between the observed and calculated values of pavement deterioration parameters. The calibrated values were further validated, and it was deduced that the HDM-4 models predict the pavement distress with high accuracy and can be further used for developing effective management and maintenance strategies for the Indian urban road network

Paper on validation of the HDM crack initiation, progression, rutting and roughness models for Macedonia.

Report describing how the vehicle operating costs were updated for New Zealand's economic analysis manual.

The current study focuses on options to improve vehicle energy efficiency by reducing rolling resistance on Dutch national highways. Different studies of pavement materials have been evaluated, and models have been compared to experimental data to review rolling resistance indicators. The study shows that texture parameters MPD (mean profile depth) and RMS (root mean square) are relevant indicators for rolling resistance, whereas the effect of road roughness (IRI) is found to be larger than indicated in the evaluated models. The effects of other wavelength regions, texture orientation, and road wear need further investigation. Switching to DPAC 2/6 for highways would result in energy savings of 2–2.5%. These calculations are based on estimations and results with high uncertainty and should therefore be taken as a rough estimate of the potential energy savings. Further research is recommended to further refine and validate the results of this study.

This paper presents a case study where a level 1 calibration has been carried out for a State Highway in Uttar Pradesh, India. The climatic condition of the site is under humid, hot and high monthly precipitation throughout the year. Two methods have been proposed to find out the calibration factors. The calibration factors namely roughness age environment, crack initiation and crack propagation are found to be 0.650, 0.970 and 1.030 respectively for the case study using method 1 calibration method and 0.650, 0.864 and 1.157 respectively using method 2 calibration. Economic analysis has been carried out taking default calibration factors and level 1 calibration factors and NPV (net present value) and IRR (internal rate of return) were found Rs. (million) 368.1 (26.5 %) and 422.4 (27.9 %) respectively. Level 1 Calibration involved desk study and many default values have been adopted but the major factors like roughness age environment, crack initiation and crack propagation are important to simulate local condition. A well calibrated model for this local condition would reduce the possibility of future funding shortages. Level 1 calibration may be carried out easily based on few secondary data within few weeks and useful for economic analysis, prioritization and budgeting for maintenance of the road network.

Deterioration models allow road managers to assess current condition and to predict future conditions of their road networks. Due to heavy vehicle axle repetitions and the effect of environmental factors, permanent deformation (rutting) develops gradually in the wheel paths and impacts on structural and surface performance of flexible pavements. This paper reports the approach adopted to develop absolute deterministic models for permanent deformation of low volume roads. A representative large sample network (23 highways) of light duty pavements was selected. For each section, time series data from four consecutive condition surveys were collected. Multiple regression analysis was carried out to develop models to predict pavement rutting progression over time as a function of a number of contributing variables. They include traffic loading, pavement strength, climate and drainage condition. For more powerful prediction, family group data-fitting approach was utilised to estimate future rutting progression based on the average rut depth curve for a series of pavements with similar characteristics. This study highlighted that separate family deterioration models are preferred and needed for more realistic results. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data with low standard error values. Also, study results show that higher traffic loading, lower pavement strength, poor drainage and climates with high seasonal variation contribute to increasing rutting progression rate.

A reliable pavement performance prediction model is needed for road infrastructure asset management systems or pavement management systems. In this study, the data on roughness progression of asphalt pavements in the long-term pavement performance (LTPP) database was analyzed in order to develop such a model. The international roughness index (IRI) is a reasonable measure of the ride comfort perceived by occupants of passenger cars and hence used as the basis for the pavement performance prediction model developed in this research. A quantitative relationship between roughness progression and accumulative traffic load, structural number, annual precipitation, and freezing index was developed and validated. Five pavement performance levels were developed to express the extent of asphalt pavement deterioration. This is coupled with a reliability analysis based on the Weibull model to estimate the remaining service life of asphalt pavements. Effective treatments of pavements at the project level for each condition state level were also proposed, which can aid network level optimization of the overall condition and corresponding budget allocations.

The integration of material-science based performance models obtained from laboratory performance testing and modelling into life-cycle-assessment of road pavements is a future oriented approach for the improvement of  performance prediction. This shall significantly improve the selection processes for maintenance strategies within pavement management as well as during the design of new pavements. Maintenance options can be selected based on material behaviour and improved prognosis of long-term performance of the pavement structure. Within the ERA-NET ROAD II project InteMat4PMS – ‘Integration of Material-science based performance models into life-cycle-analysis processed in the frame of Pavement Management Systems’ – this
approach was developed and tested in practice on two test sections in Germany. The output of this project is presented in this paper.

Deterioration forecasting modeling is an essential element for an efficient pavement management system. The HDM-4 (Highway Development & Management-4) model developed by the World Bank is widely distributed to more than 100 countries around the world. However, many users often point out problems related to calibration limitations, and question the reliability of their results due to the extremely large number of variables, and difficulty in the calibration procedure of deterioration  models in the HDM-4. The current calibration method based on the Network-based approach which was introduced by the HDM-4 developer and has several limitations in describing the precise deterioration progress, and practical application. In fact, many HDM-4 users often give up implementation due to these reasons. To mitigate these problems, this paper suggests an improved calibration method for the HDM-4 deterioration models relevant to the deterioration speed and shape of the curve. The benefits are not limited to only high precision calibration, but also easy application by minimum data, and covering problems on incomplete pavement inventory data which are considered the most serious problems in the application of the HDM-4. The validity of the suggested methods was empirically shown through experience with the national highways in Korea. This paper could be a good reference for the implementation of the current HDM-4 model, as well as its future improvement.

The Highway Development and a Management System (HDM-4) developed by World Bank is a powerful pavement management software tool capable of performing technical and economic appraisals of road projects, investing road investment programs and analyzing road network preservation strategies. Its effectiveness is dependent on the proper calibration of its predictive models to local conditions. The use of appropriate calibration factors in HDM-4 pavement deterioration models will facilitate more reliable and rational prediction of pavement deterioration for the road network under considerations. This in turn will help in better assessment of the maintenance and rehabilitation requirements of pavements and improved pavement management system. In the present study, computer programs in ‘Visual C’ language have been developed for calibration of pavement deterioration progression models stipulated in HDM-4 tool such as cracking, ravelling, edge break and pothole for surface treatments with unbound base types of pavement composition used for Low Volume Roads (LVR) in India.

Paper describing calibrating HDM-4 for China Taiwan.

One of the key challenges for a road concessionary is to be able to predict its roadway network´s pavement performance with high accuracy, which, in turn, has a significant impact on the pavement management actions to be taken during the concession period. An impediment to a more common use of models to predict a pavement’s performance in Brazil is lack of detailed historical information for calibrating performance models to local conditions. In the case of a concessionary, however, extensive detailed information regarding their roadway network is available. This study was conducted to calibrate pavement performance models in Highway Development and Management Model for the portion of Highway SP-280 under the administration of the concessionary Companhia de Concessões Rodoviárias (CCR) SPVias based on its historical data and to predict future pavement performance based on the calibrated models. Models were calibrated for an asphalt made with rubber modified bitumen and a cape seal and their roughness and cracking parameters progressed with time.

This is a paper on adapting the HDM-4 rut depth model to enable improved predictions of the impact of climate change on pavement deterioration.

I have reservations on including this paper at the site because the authors make a fundamental mistake with regard to HDM-4 and its modelling approach. When we developed the pavement deterioration models for HDM-4 we tried to balance the ability to predict pavement deterioration with the tractability of applying the models. If one increases the number of variables in a model it will always result in improved predictions. HDM-4 contains the right balance.

The approach here is not viable for any network type applications since not only is it impossible to get data on asphalt softening point and the voids in mix, but even if you were looking at a discrete section of road the variability of these variables would be significant within the section.

So caveat emptor with the paper!

Series of reports from the NordFu project which developed project and network level models, including calibrating HDM-4 to cold climates.

In this paper, a model was developed for the pothole in the flexible pavement with respect to the increase in the cumulative traffic axle load in order to predict quantities and estimate cost of repairs in a pavement stabilization program. The progression, in the area of the pothole at two locations in the semi urban portion of the Ajasse po – Ilorin intercity road in Nigeria and the corresponding traffic were monitored continuously for a period of eight weeks. The statistical regression analysis of the percentage increase in the area against the cumulative traffic axles was performed with the ‘Liness Microsoft Excel’ software. The model characteristics (coefficient and the constants) are 0.001 – 0.0015 m2/ standard axle and 11.85 – 12.68 m2 respectively at R - squared value of 0.98. The application of the model for the preparation of economically justifiable road rehabilitation and maintenance program was demonstrated in the paper.

Interesting paper comparing Ireland's PMS models with HDM, and New Zealand's experieinces.

Ireland has a national road network of approximately 5300km which is managed by Transport Infrastructure Ireland (TII). TII create yearly pavement maintenance and renewal programmes using a Pavement Asset Management System (PAMS). Accurate pavement deterioration models and reset values are an essential part of a PAMS and are required for life cycle cost analysis (LCCA). Pavement maintenance and renewal schemes are prioritised based on the LCCA's largest benefit to cost ratio, thereby optimising the annual pavement maintenance and renewal budget. Currently, TII implement pavement deterioration models based on models used in Austria and Belgium, with modifications appropriate to Irish conditions. The reset values in use are based on best estimates of expected treatment effects and were not initially based on the measured post-treatment condition. This research aims to refine and improve the deterioration models currently in use and to calibrate the treatment reset values using measured pavement condition on treated sections of pavement. Several long-term pavement performance (LTPP) monitoring sites were selected for the analysis. The LTPP monitoring sites consist of newly constructed and recently maintained pavement sections throughout the Irish national road network for each subnet category. The international roughness index (IRI), rut depth and longitudinal profile variance 3m (LPV3), measured annually from 2010 to 2019, were analysed and compared to the current PAMS's pavement reset values and deterioration models. Generally, the measured reset values of the LTPP monitoring sites were lower than the TII's PAMS reset values, indicating that TII's PAMS may underestimate the treatment benefit for the LCCA treatment prioritisation process. The measured pavement deterioration rates were also typically lower than the predicted pavement condition values of TII's PAMS. This research concludes that an update to the PAMS, using better calibrated deterioration models and reset values would be highly beneficial. The LTPP monitoring should be continued to assess the longevity of the applied pavement treatments and consequently, determine the full deterioration model for each of the LTPP monitoring sites into the future.

A review was undertaken by to establish whether or not passenger car and truck (HCV-I) vehicle operating cost (VOC) – roughness cost tables and graphs contained in Transfund New Zealand’s Project Evaluation Manual (PEM) are valid for current, New Zealand, operating conditions. This indicated significant overestimation of the maintenance and repair costs.

This report documents the calibration of HDM-4 RD models for sealed granular and asphalt
pavements based on SRA historical deterioration data. SRAs supplied historical roughness and
rutting deterioration data and some supplied cracking deterioration data and maintenance history.
HDM-4 RD models were calibrated to suit conditions in Victoria, Tasmania, South Australia,
Queensland and New Zealand. Rutting and roughness RD models were calibrated for all these
SRAs, except Queensland. Cracking RD models were calibrated for South Australia due to the
reasonable quality of its cracking data. Cracking data from Victoria, Tasmania and New Zealand
were either of inadequate quality or too insignificant, in terms of extent of cracking, to be
considered in the analysis, hence cracking models were not calibrated for the data from these
authorities.

Report describing comparision of in-situ pavement deterioration from LTPP sites with the CAPTIF test track. The annex to the report can be downloaded here.

The aim of this research, carried out in 2005, was primarily to test the current pavement deterioration models adopted in the New Zealand system. Most of these models were adopted from HDM-III and HDM-4, but some locally developed models were also tested.

Cambodia HDM-4 training course. 9/10.

The NZVOC Model is used by Transfund New Zealand to prepare tables of vehicle operating costs for their Project Evaluation Manual. Two projects were conducted to update the costs and develop a new version of the NZVOC Model, one in 1999 and a second in 2001-2003. The NZVOC model contains enhanced VOC relationships and formed the basis for the HDM-4 RUE model.

The NZVOC Model is used by Transfund New Zealand to prepare tables of vehicle operating costs for their Project Evaluation Manual. Two projects were conducted to update the costs and develop a new version of the NZVOC Model, one in 1999 and a second in 2001-2003. The NZVOC model contains enhanced VOC relationships and formed the basis for the HDM-4 RUE model.

The NZVOC Model is used by Transfund New Zealand to prepare tables of vehicle operating costs for their Project Evaluation Manual. Two projects were conducted to update the costs and develop a new version of the NZVOC Model, one in 1999 and a second in 2001-2003. The NZVOC model contains enhanced VOC relationships and formed the basis for the HDM-4 RUE model.

Presentation to the 2001 PMS Conference on how to calibrate HDM-4.

Article on PIARC magazine on the calibration of HDM-4 to Eastern Europe.

Presentation on how to calibrate HDM. Accompanies a paper by the same name for the 1st European PMS Conference.

Presentation on how HDM-4 calibration and validation is done.

Authored by Chris Bennett and Bill Paterson, the HDM-4 Series Volume 5 describes how to calibrate HDM-4. The report addresses a range of issues from Information Quality through calibrating pavement deterioration and road user effects.

Calibrating the free speed and congestion speed model to Thailand

Calibrating the free speed and congestion fuel models to Thailand

Report describing calibration and application of RUE models for New Zealand

HDM-4 RUE Model calibration done as part of the Thailand Central Database Project

A review of how HDM-III was used in studies in different countries

A review of how HDM-III was used in studies in different countries.

Low Volume Roads Conference. Application of HDM-III

Calibration of the HDM-4 road user effects model to Lesotho.

A report on establishing VOC and pavement deterioration relationships for India. Contains a detailed review of the India VOC and PDWE research and how this work was used to establish models for use in the dTIMS PMS application.

A report on establishing VOC and pavement deterioration relationships for India. Contains a detailed review of the India VOC and PDWE research and how this work was used to establish models for use in the dTIMS PMS application.

Short note on modified version of HDM-III for Thailand

How HDM-III was modified and used for a study in Myanmar. Covers VOC and PDWE calibration as well as roughness measurements and application of HDM

How HDM-III was modified and calibrated to Myanmar for the Comprehensive Transport Study.

Road Research Unit Bulletin 82. This is the first NZVOC Model which was used to generate the vehicle operating costs for the Project Evaluation Manual.