PAVEMENT MANAGEMENT SYSTEM FOR LOW VOLUME ROADS Submitted in partial fulfilment of the requirements of the degree of Master of Technology in Transportation Engineering by Koorma Rajendra Babu Roll No. 111710 Supervisors: Dr. Venkaiah Chowdary Assistant Professor Department of Civil Engineering and Dr. D.S.N.V. Amar Kumar Assistant Professor Department of Civil Engineering
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PAVEMENT MANAGEMENT SYSTEM FOR
LOW VOLUME ROADS
Submitted in partial fulfilment of the requirements
of the degree of
Master of Technology
in Transportation Engineering
by
Koorma Rajendra Babu
Roll No. 111710
Supervisors:
Dr. Venkaiah Chowdary
Assistant Professor
Department of Civil Engineering
and
Dr. D.S.N.V. Amar Kumar
Assistant Professor
Department of Civil Engineering
Transportation Division
Department of Civil Engineering
NATIONAL INSTITUTE OF TECHNOLOGY, WARANGAL
AUGUST 2012
1. INTRODUCTION
1.1 General
Low Volume Roads (LVRs) constitutes an integral component of the road system in all
countries. Their importance extends to all aspects of the social and economic development of
rural communities. It is known that on a world-wide basis the number of low traffic roads far
exceeds the mileage of high traffic roads. India has a road network of over 4.32 million
kilometers in 2011, the third largest road network in the world. The LVRs in India forms a
substantial portion of the total road network. 3.11 million kilometers of road network was the
contribution of LVRs in India in 2011 which was 72% of the total road network length
(source: Indian Road Network, Wikipedia website). In view of this they often form the most
important link in terms of providing access to educational, medical, recreational and
commercial activities in local and regional areas. Universally, there is no exact definition for
Low Volume Roads (LVRs), but it could be defined primarily as a type of transportation
system typically constructed to manage or extract resources from rural or undeveloped areas.
These unique systems are designed to accommodate low traffic volumes with potentially
extreme axle loads. They are commonly defined as having less than 400 ADT (Average Daily
Traffic).
In the recent past, Government of India (GoI), with the initiation of the ambitious programme
Pradhan Mantri Gram Sadak Yojana (PMGSY) gave great importance to low volume roads
realizing their role in the economic development of rural areas. The vast expansion of the road
network has brought connectivity to the rural areas of the country. Majority of these roads are
constructed as flexible pavement with a thin bituminous surfacing layer of Open Graded
Premix Carpet (OGPC) of 20 mm as per the guidelines given in IRC:SP:20 (2002) and
IRC:SP:72 (2007). Current methods that are used for maintenance of these roads are based on
the judgment and experience of engineers, without considering the actual pavement
performance data. Regular maintenance would minimize not only wastage of financial
resources but also other resources such as equipment, manpower and materials. Earlier studies
reported that, the maintenance cost of a road which is in a very poor condition is four to five
times the cost if a pavement is regularly maintained while it is in a good condition (Haas et al.
1994). The allocation of budget towards maintenance of low volume roads are always on the
lower side, when compared with the high volume roads. Further the tendency is to neglect
those roads which are in low traffic volume and low composition of heavy commercial
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Vehicles. This has led to different procedures to be adopted for maintenance of LVRs and
therefore the allocated resources should be used wisely.
Pavement management has progressed from 1960’s to current widespread and successful
application in many countries around the world. And also there are “reinvention/invention”
needs involving succession planning, integration, adaption to privatization, longer lasting
pavements, performance models, quantification of benefits, incentive programs and very long
term life cycle analysis which have to be addressed if progress in pavement management is to
continue. According to Haas and Hudson (1978), “A Pavement Management System –
encompasses a wide spectrum of activities including the planning of programming of
investments, design, construction, maintenance and the periodic evaluation of performance.
The function of management at all levels involves comparing alternatives, coordinating
activities, making decisions and seeing that they are implemented in an efficient and
economical manner”. For effective PMS asset management is very important. Federal
Highway Administration (FHWA) and American Association of State Highway and
Transportation Officials (AASHTO) (1997) defined asset management as follows: “Asset
management is a systematic process of maintaining, upgrading and operating physical assets
cost-effectively. In the broadest sense, the assets of a transportation agency include physical
infrastructure such as pavements, bridges, and airports, as well as human resources (personal
and knowledge), equipment and materials, right-of-way, data, computer systems, methods,
technologies and partners”. With this background, in the present study, an effort is made to
develop Pavement Management System (PMS) for Low Volume Roads elevating the need of
Life Cycle Cost Analysis and Optimum Maintenance and Rehabilitation Strategy for the
same.
1.2 Low volume road scenario in India
During the year 1978, a working group was set up a planning commission for providing
information weather connectivity was established to all the villages of India (Planning
Commission, PEO, and Report No.:201, 2010). During the 1980s, Indian Road Congress
(IRC) conducted studies on the rural roads with the main objective to find out and quantify
the possible impact of roads on the socio economic development of rural areas. The survey
conducted in remote areas in India by Central Road Research Institute (CRRI) reported that
the villages located on the main road are comparatively well developed than those away from
the roads. These roads connecting different villages were made up of moorum or other locally
available granular materials of low quality standards and were built up by stage construction.
No pavement design procedure was adopted for construction of such roads. During the eighth
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five year plan (1992-97) priorities were accorded to link all villages with a population of 1000
and above to accelerate village connectivity.
Till the launching of PMGSY, the roads covered only 60% of villages/habitations in the
country. Understanding the various direct and in direct roles that low volume roads play, the
Government of India on 25th December, 2000 launched the PMGSY in order to provide road
connectivity, through good, all weather roads, to all rural habitation of targeted population.
At the commencement of PMGSY, it was estimated that about 3,30,000 habitations out of
8,25,000 habitations were without all-weather road connectivity, which means that about 40%
of the habitations were cut-off from the main stream development. Subsequently, it was
proposed to take up 1,73,000 unconnected habitations of population above 500 (250 in case of
hill, desert and tribal areas) under the PMGSY. Under the program 31,924 unconnected
habitations have been connected with the total constructed road length going up to 1,46,200
kilometers. About 1,55,000 kilometers existing rural roads have also been upgraded. It is
targeted to provide all weather connectivity to all habitations having a population of more
than 500 and more than 250 in hill states, tribal and desert areas by 2012.
1.3 Maintenance of low volume road
The development of low volume road received little attention in the various five year plans.
These plans largely concerned themselves with national highways or trunk roads. In 1967, a
special committee was set up to examine the status of rural roads and to suggest a suitable
development policy (11th five year plan working group on rural roads, 2006). This committee
perceived the crucial role of these roads in the context of speedy socioeconomic development
of the countryside. The fifth five year plan (1975/76 to 1979/80) envisaged a minimum needs
program for the villages, which contained road needs as one of its segments mandated that all
villages with a population of 1000 or more should have an all-weather road. In the seventh
five year plan document (1985-1990) the importance of low volume roads were constructed
under various rural road development programmes, which were mainly conceived for
employment generation and poverty alleviation. In such programmes serious efforts were not
made to build sustainable all weather roads with proper maintenance strategies (11 th plan,
GoI). It would not be out of recall that a World Bank study in 1988 demonstrated that
spending one rupee on road maintenance would have saved three rupees in rehabilitation.
In India, many of the low volume roads do not receive any funds for maintenance. Even if the
funds are available, various maintenance tasks and frequency is not clearly defined. Currently
the funds for rural roads are allocated based on the kilometer basis without much
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consideration of actual maintenance requirements which depends upon the traffic volume,
composition, terrain, environment, and drainage and subgrade condition. As a result the
system has started showing signs of premature failure. Huge funding is needed to bring the
system to desired serviceability level. In addition, low volume road agencies struggle with
limited staff, skills, equipment and information on pavement condition.
Although materials and techniques for pavement maintenance have improved, more research
is essential in the area of policy development for the effective management of pavement
maintenance, specifications development, cost-effective treatments and the best applications
of treatment timing. Many factors must be evaluated to select pavement maintenance
treatments. The factors may include cost of treatment, type, extent of distress, traffic volume,
climate, pavement type etc.
2. REVIEW OF LITERATURE
Kirori et al. (2001) suggested structure of the comprehensive road database for existing
flexible pavements to suit Indian highway engineers and provide inputs o maintenance work
planning modules under various budget scenarios. The dROAD (for road database) &dTIMS
(Total Infrastructure Management System for Database) software have been used. In this
study database mainly contains inventory, condition, traffic and strength perspectives with
140 data fields and 33 tables developed for coding. The roughness data have been collected
by axle mounted Bump Integrator and distress data by visual assessment. The structural
evaluation of pavement is presented in terms of Modified Structural Numbers (MSN) using
deflection-based relationships, though the relationship needs to be reviewed. The deterioration
models, Vehicle Operating Cost (VOC) equations have been adopted from different projects.
In various Pavement Management System (PMS) research/studies/projects, the condition
survey involved cumbersome exercise measuring cracked, raveled, potholed area, etc.
manually or visual condition rating and thus limited to smaller networks despite sincere and
precise works.PMS developed using comprehensive road database is based on ‘Life Cycle
Cost’ concept that includes construction cost, maintenance cost, rehabilitation cost and user
cost over the life of pavement. From the study conducted it was observed that Decision
Supporting System must be enhanced more to allocate budget on road network and there is a
need to standardize the classification of existing pavements on the basis of MSN with respect
to commercial vehicles per day.
Dhaliwal and Tipnis (2004) proposed the rehabilitation works for a disused airfield,
constituting a prestigious project, have been designed and planned by Military Engineers in
the recent past. Structural evaluation, functional evaluation and evaluation of existing 4
pavement facilities have been carried out despite of lack of information of pavement design
and construction records and the overlay design of the air field pavements was suggested in
this study based the condition of the pavement distress and severity of the distress type. The
construction alternatives that are considered during the air field pavement management are as
follows (i) complete removal of existing pavement and reconstruction of the pavements from
the subgrade, (ii) removal of badly damaged/failed pavement (approximately 35 % of existing
pavement), its reconstruction from the subgrade and re-strengthening overlay for the
remaining portion of airfield pavements, (iii) constructing of overlay for all airfield
pavements, utilizing the same as sub-base. Alternative (ii) was considered as most economical
solution considering initial construction cost and would suffice the design safety
considerations, if executed carefully. Alternative (i) would be obviously ideal solution, but
would have been very costly, though in long terms of life cycle costs, the alternative would
prove to be economical. Alternative (iii) would not have catered for the crucial safety aspects
and also would entail extensive and time consuming crack repairs, delaying the overlay
construction and thus lead to increase of the time related costs.
Aggarwal et al. (2004) developed a Pavement Management System for an identified National
Highway Network to assist the highway engineers responsible for maintaining the highway
network as well as the authorities responsible for allocating funds, in making consistent and
cost effective decisions, related to maintenance and rehabilitation of pavements. To predict
most economical maintenance strategy for a particular pavement section and prioritization of
maintenance activities in the event of a constrained budget. The pavement deterioration
models incorporated in HDM-4 have been calibrated to adapt to local conditions and suitable
calibration factors have been determined. The pavement deterioration models incorporated in
to HDM-4 have been calibrated using the pavement condition data collected on the pavement
sections and calibration factors for various deterioration models such as cracking, raveling,
potholing and roughness models have been obtained. Under project level PMS analysis, the
optimum Maintenance and Rehabilitation (M&R) strategy for a pavement section has been
determined on the basis of highest Net Present Value (NPV) / Cost ratio, amongst a number
of pre-defined M&R strategies. The average roughness value of the highway network keep on
increasing with gradual reduction in budget levels, which in turn may lead to very high road
user cost values.
Kandhal (2008) discussed the effective method for the repairing of the potholes in India. An
economical generic, readymade stockpile cold patching mix has been proposed as a part of the
experimental study. The generic mix can be placed without preparing the pothole, such as,
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drying, squaring the edges, cleaning and tack coating. The mix can be stockpiled and remains
workable for at least 6 months. The desirable characteristics of generic cold patching mix are
one-sized aggregate, use of least absorptive aggregate, adequate binder content and proper
amount of anti-stripping agent.
Bezabih and Chandra (2009) developed mathematical models to obtain Axle Load
Distribution (ALD) on a highway from its vehicle volume count. And ability to convert the
soil sub-grade strength given in terms of CBR in to modulus of subgrade reaction (k), and a
traffic load given in terms of Million Standard Axles (msa) in to ALD makes it possible to
design the two types of pavements for the same soil and traffic conditions. It was observed
from the models developed that flexible pavements show wider range of variation in cost with
respect to design parameters of traffic and soil CBR of which when compared to the rigid
pavements variation in cost is small. Flexible pavements are more economical for the lesser
volume of traffic.
Lee et al. (2009) developed a model equation to represent various pavement distresses such as
crack, rutting, roughness, etc. as one combined index in order to manage the pavement of
Korean asphalt national highway system at network level. Additionally, the threshold values
for rut depth and crack percent for resurfacing were determined to follow the
recommendations of pavement evaluation panel experts. The research method for the
development of NHPCI (National Highway Pavement Condition Index) involved selection of
the sample size and research subject area of pavement. Then, an automated road analyzer for
the investigation of pavement condition was used to measure the pavement condition
quantitatively. Afterwards panel experts qualitatively evaluated the measurement for a
multiple regression analysis. Moreover, the threshold value for pavement resurfacing was set
at 50% of the value recommended by the panel based on the rehabilitation strategies required
by the pavement evaluation card and the result of influential factors for the selection of
rehabilitation strategy. The study resulted in R2 value of 0.78 for the NHPCI model equation
developed in this study, and sensitivity analysis revealed that roughness (International
Roughness Index) and crack percent were sensitive. Finally, this study recommends average
rut depth value of 11 mm, crack percent of 20% as the threshold values for the pavement
resurfacing (overlay), and average rut depth value of 12 mm as threshold value for the
pavement mill-resurfacing (inlay).
Danial et al. (2010) used MicroPAVER software which is most comprehensive pavement
management software. Implementation of different budget scenarios provided in this software
such as: unlimited budget, annual budget, etc., as well as practical methods of maintenance
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and other unique features help the decision makers to successfully manage the pavements on
both network and project level by examining various trade-offs between allocated budgets. In
this study 10 main streets were studied and 131 pavement sections were investigated. The
average weighted condition for each branch, during a design period of five years, was
indicated to compare the effect of three different allocated budgets. Ten deterioration
prediction models were developed for the study network. Based on the average PCI for the
entire network the budget needed to maintain Weighted PCI for all branches was also
calculated using MicroPAVER software.
Qiang and Ling (2010) discussed the management and rehabilitation strategy of the pavement
network in china using the Discrete Optimization Techniques and proposed four discrete
optimization models which are formulated using integer programming with binary decision
variables. The objective function and constraints are based on the pavement performance and
prediction model using the Pavement Condition Index (PCI). Numerical experiments are
being in operation in Sichuan Province using four optimization techniques showing feasibility
and effectiveness of the proposed models.
Kobayashi et al. (2010) have proposed Deterioration forecasting modeling for an efficient
pavement management system. There is a problem for the accurate prediction of road
deterioration due to quality of pavement performance data and the different pavement
structural, material and environmental conditions. In this paper a methodology to estimate the
Markov Transition probability model is presented to forecast the deterioration process of road
sections. The deterioration states of the road sections are categorized in to several ranks and
the deterioration process are characterized by hazard models. The Markov transition
probabilities between the deterioration states which are defined by the non-uniform or
irregular intervals between the inspection points in time are described by the exponential
hazard models. In this paper, traffic-related data (ESAL) and Structural Number (SN) are
employed to estimate the exponential hazard model be expanded in various factors such as
temperature, pavement structure (type, layer thickness and modulus resilient of the sub grade)
and environmental variables.
Kirbas and Gursoy (2010) performed case study on developing a Pavement Management
System for the selected road sections. Pavement Management is in a broader sense, a working
program that involves all the procedures of planning, programming, designing, building,
maintaining and rehabilitation. A PMS arranges tools and methods to be used for determining
the best maintenance schedule for the decision makers in a given period. In this study
infrastructure distress data which is compatible with the distress identification manual
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published by American Society for Testing and Materials in 1999 is collected from 20
sections selected from the arterial road network in Besiktas district of Istanbul. The reasons
for the formation of distress types in the determined network are studied under the headings
like axle load, climate and other (material characteristics), and distress evaluations throughout
the whole network and each section are carried out. Paver system which is pavement
management system at several airports and cities/towns of USA and at different countries
which is developed during 1970’s by U.S. Army Corporation of Engineers. Paver system use
Pavement Condition Index (PCI) for determining current circumstances in pavement section.
Dattatraya (2011) presented the timely identification of undesirable distress in pavements at
network level using pavement management system. This paper summarizes the
implementation of a pavement condition prediction methodology using the Artificial Neural
Network (ANN) to forecast cracking, raveling, rutting and roughness for Low Volume Roads
(LVR) in India. Road Inventory data, as well six cycles of pavement performance data that
include distresses, subgrade characterization and traffic data, were collected from 61 in-
service LVR pavement sections over a 3 year period in India. ANN models with different
architectures were trained and tested to suggest the optimum ANN model. The study results
suggest that ANN models satisfactorily forecast future individual distresses. The performance
of the suggested ANN models is also compared to the calibrated HDM-4 models. The
suggested ANN models shows a high goodness of fit between observed distress and ANN
predicted distresses of more than a ratio of 0.98 for cracking, raveling, rut depth and
roughness progression models at the testing stage. The ANN models show a higher goodness
of fit regarding the predictability of distresses than that of HDM-4 calibrated distresses. This
is true for all four different ANN models, proving the success of ANN models over HDM-4
pavement deterioration models in predicting distresses. The suggested ANN models will be
useful in the accurate prediction of cracking, raveling, rut depth, and roughness. The models
can calculate the appropriate time for various maintenance strategies to preserve the huge
network of LVR in India and other developing countries with similar environmental and
traffic conditions.
Do (2011)produced methodology to estimate the mean life and failure probability in
consideration of road functional characteristics based on parametric and non-parametric
estimation models. Based on the three types of functionally classified roads: urban, rural and
recreation roads, five different lifetime distributions were tested: normal, lognormal,
exponential, weibull and loglogistic to select the appropriate probability distribution and to
estimate mean life and failure rates. The goodness-of-fit test, such as the anderson-darling
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test, was performed to select optimal probability distribution as a result of which approximate
distribution of each case was selected: lognormal distribution for rural roads and weibull
distribution for recreation roads. Non parametric estimation method for rural roads was
applied because there is no approximate probability distribution for rural roads. In this study
using probabilities it was found that mean life for urban, rural and recreation roads are about
6.8 years, 9.2 years and 9.5 years respectively for national highways in Korea.
Giustozzi et al. (2012) discussed the innovative methodology to evaluate the environmental
impact of preventive maintenance activities which relates the performance and cost during the
service life of the pavement through a multi-attribute (life cycle cost, performance and
environmental analysis). Performance deterioration models were used to identify the time
where preventive maintenance activities were needed based on pre-established threshold.
Three Pavement Management treatments that were considered were micro-surfacing, slurry
seal and thin overlay. Through this study it is also evident that less energy emission and CO2
during the process of operation of the maintenance strategy having eco-advantage.
Santos and Ferreira (2012) presents a new Life Cycle Cost Analysis (LCCA) system based on
an optimization model considering pavement performance, called OPTIPAV, developed and
programmed to help pavement designers to choose the best pavement structure for a road or
highway. LCCA system considers AASHTO serviceability concept. OPTIPAV program uses
minimization of the cost of maintenance of the pavement based on the Present Serviceability
Index (PSI) and adopts classified pavement structure based on the Structural Number (SN)
and Traffic Volume in terms of ESALs.
Chen et al. (2012) discusses the function design and the application effort of using GIS and
GPS in the system. The practice shows that the pavement inspection time is reduced greatly
because of the geospatial tools available for the maintenance and rehabilitation works and to
optimize pavement maintenance decisions. Pavement is divided in to sample units based on
the functional classification and individual sample units are examined thoroughly for the
measurement of distress and its extent to enter in to Geographical Information System(s).
From this study it is observed that using GIS leads to a multilevel analysis techniques for the
optimum management of Pavement Maintenance.
3. SUMMARY
All the developed distress prediction models should be subjected to measures of adequacy
before adoption and implementation in a Pavement Management System (PMS).Using of
Global Positioning System (GPS) when recording the distress data greatly increases the
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pavement management benefits. Pavement Condition Index methodology is used in many of
the developed countries for the pavement evaluation. Pavement Serviceability Index (PSI) and
Structural Number (SN) of the pavement are used as the parameters to reduce the
maintenance and rehabilitation costs. Life Cycle Cost Analysis (LCCA) of pavement
considers the serviceability concept adopted by the American Association of State Highway
and Transport Officials (AASHTO) for use in the design of flexible pavements. Discrete
optimization model uses PCI values as a main representative factor for the individual
pavement section units. A multi-attribute approach for life cycle assessment is needed to
evaluate the implications of incorporating the environment in to the decision making process,
in addition to cost and performance. Use of cold patching was adjudged as the best performer
in the readymade mix category in a nationwide field evaluation research project conducted
under the Strategic Highway Research Program (SHRP).The Markov transition probabilities
between the deterioration states, which are defined by the non-uniform or irregular intervals
between the inspection points in time, are described by the exponential hazard models. Based
on the deterioration rate the probability of failure of the pavement can be calculated using
which the suitable pavement maintenance and rehabilitation strategy was adopted. The road
network data collection in the field was divided under the following heads: (i) inventory data,
(ii) structural evaluation (structural capacity), (iii) functional evaluation (pavement condition
and riding quality) and (iv) evaluation of pavement materials. There should be an efficient
historical data base for developing of the regression models for pavement performance
prediction for kind of distresses. Including the Road User Cost Studies (RUCS) in the
development of PMS can lead to efficient Life Cycle Cost Analysis of pavement after the
maintenance and rehabilitation works. Road projects undertaken by any government agency
should be thoroughly verified by benefit to cost ratio because of socio-economic project
dispensing and to reduce frequency of road maintenance through various maintenance and
rehabilitation works.
4. REFERENCES
1) Aggarwal, S., Jain, S. S., and Parida, M. (2004). “Development of pavement management
system for Indian national highway network.” Journal of Indian Road Congress, 65(2),
271-326.
2) Bezabih, A. G., and Chandra, S. (2009). “Comparative study of flexible and rigid
pavements for different soil and traffic conditions.” Journal of Indian Road Congress, 70,
153-162.
3) Chen, W., Yuan, J., and Li, M. (2012). “Application of GIS/GPS in Shanghai airport
pavement management system.” International Workshop on Information and Electronics 10