Scholarly article on topic 'Adaptation of HDM-4 Tool for Strategic Analysis of Urban Roads Network'

Adaptation of HDM-4 Tool for Strategic Analysis of Urban Roads Network Academic research paper on "Civil engineering"

CC BY-NC-ND
0
0
Share paper
Academic journal
Transportation Research Procedia
OECD Field of science
Keywords
{"Urban roads" / HDM-4 / "Strategic analysis" / "international roughness index."}

Abstract of research paper on Civil engineering, author of scientific article — U. Shah Yogesh, S.S. Jain, Tiwari Devesh

Abstract The Urban roads constitute about 9.0% (4.11 lakh kms) of the total road length in India. The urban roads especially in metropolitan cities carry a huge traffic volume which affects the road condition adversely. The other factors responsible for poor roads in urban areas are the problem of overloading, encroachment on the road land and ribbon development along road side, lack of attention to drainage which may lead to failure of pavement, and various utility services which necessitate frequent digging thereby disturbing homogeneity of pavement. Therefore, there is a need of an efficient Urban Pavement Maintenance Management System (UPMMS) which would be useful to the highway agencies in planning pavement maintenance strategies in a scientific manner for urban cities, to ensure rational utilization of limited maintenance funds. This paper describes the adaptation of the World Bank's highway development and management model HDM-4 at the strategic level. Urban road network of 21 sections, consisting of total 60 km road length of Noida city, near New Delhi, capital of India, were analyzed. The analysis was carried out to maximize the net present value (NPV) and minimize the costs to achieve a desirable target international roughness index (IRI). The analysis results presented the need for the optimal capital and recurrent maintenance required to maintain the urban road network in serviceable condition. The urban roads can be managed and maintained effectively using the strategy application of HDM-4.

Academic research paper on topic "Adaptation of HDM-4 Tool for Strategic Analysis of Urban Roads Network"

Available online at www.sciencedirect.com

I^^P1 ScienceDirect

ELSEVIER

Transportation Research Procedía 17 (2016) 71 - 80

11th Transportation Planning and Implementation Methodologies for Developing Countries, TPMDC 2014, 10-12 December 2014, Mumbai, India

Adaptation of HDM-4 Tool for Strategic Analysis of Urban Roads

Network

Shah Yogesh U.a*, Jain S. S.b and Tiwari Deveshc

aAssociate Professor, Department of Civil Engineering, Marwadi Education Foundation, Rajkot- 360009, Gujarat, India bProfessor of Civil Engineering & Associate Faculty CTRANS, Indian Institute of Technology Roorkee, Roorkee — 247667, Uttarakhand, India. cPrincipal Scientist & Group Coordinator, Road Asset Management Group, Central Road Research Institute (CRRI), New Delhi, India

Abstract

The Urban roads constitute about 9.0 % (4.11 lakh kms) of the total road length in India. The urban roads especially in metropolitan cities carry a huge traffic volume which affects the road condition adversely. The other factors responsible for poor roads in urban areas are the problem of overloading, encroachment on the road land and ribbon development along road side, lack of attention to drainage which may lead to failure of pavement, and various utility services which necessitate frequent digging thereby disturbing homogeneity of pavement. Therefore, there is a need of an efficient Urban Pavement Maintenance Management System (UPMMS) which would be useful to the highway agencies in planning pavement maintenance strategies in a scientific manner for urban cities, to ensure rational utilization of limited maintenance funds.

This paper describes the adaptation of the World Bank's highway development and management model HDM-4 at the strategic level. Urban road network of 21 sections, consisting of total 60 km road length of Noida city, near New Delhi, capital of India, were analyzed. The analysis was carried out to maximize the net present value (NPV) and minimize the costs to achieve a desirable target international roughness index (IRI). The analysis results presented the need for the optimal capital and recurrent maintenance required to maintain the urban road network in serviceable condition. The urban roads can be managed and maintained effectively using the strategy application of HDM-4.

© 2016PublishedbyElsevier B.V. Thisisanopenaccess article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the Department of Civil Engineering, Indian Institute of Technology Bombay Keywords: Urban roads; HDM-4; Strategic analysis; international roughness index.

Transportation Research

Procedía

www.elsevier.com/locate/procedia

* Corresponding author. Tel.: +919998978767. E-mail address: yogeshfrombaroda@yahoo.co.in

2352-1465 © 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the Department of Civil Engineering, Indian Institute of Technology Bombay doi:10.1016/j.trpro.2016.11.062

1. Introduction

Pavement management systems have improved significantly and implemented effectively in developed countries, but developing countries like India still needs a systematic approach to implement PMS efficiently. Today, highway administrators have number of tools or mechanisms that allow them to make a better use of the available resources for the M&R of highway pavements but are not acceptable globally. Hence, these tools are lacking in universal acceptance and implementation. The World Bank has developed Highway Development and Management System (HDM-4) which is an internationally recognized tool available for making timely and cost effective maintenance management decisions for urban road network. HDM-4 system could be implemented to assist the highway agencies for establishing realistic levels of funding, and to set levels and priorities to maximize the effectiveness of expenditure on pavement maintenance activities. Therefore, HDM-4 system has been selected and used in this study due to the wider international acceptance.

2. Overview of HDM-4

The Highway Development and Management System (HDM-4) system has been developed after a series of studies carried out in different countries of the world. Though initiated by World Bank in the late sixties, many leading research institutions of the world have contributed immensely in its development during last three decades. Following are the three main areas of analysis in HDM-4 which can be undertaken using the following applications (Morosiuk et al. 2006): Project analysis, Programme analysis and Strategy analysis:

i. Project Analysis: Project analysis is concerned with the evaluation of one or more road projects or investment options. It includes the appraisal of M&R options for existing roads, widening or geometric improvement schemes, pavement upgrading, new road construction, etc.

ii. Programme Analysis: Programme analysis is concerned with the preparation of work programmes in which candidate investment options are identified and selected, subject to resource constraints. Road networks are analyzed section by section and estimates are produced of road works and expenditure requirements for each section over a funding period. Programme analysis may be used to prepare multiyear rolling work programmes.

iii. Network Strategy Analysis: Strategic planning is concerned with the analysis of a chosen network as a whole. A typical application is the preparation of long range planning estimates of expenditure needs for road network development and maintenance under different budget scenarios. Estimates are produced for expenditure requirements for medium to long term periods of between 5 to 40 years.

3. Literature Review

Urban maintenance management system has been developed at network-level and project level for urban cities in developed countries (Battiato et al. 1994, Chen et al. 1994 & Sohail et al. 1996). At a later stage, Highway Development and Management (HDM-4) analysis tool, developed by the International Study of Highway Development and Management (ISOHDM), was available which was a comprehensive package used to evaluate pavement condition, to suggest optimum M&R strategies, to prepare road maintenance investment plan, and to carry out economic appraisals of road projects. The budget requirements and prediction of pavement performance by applying the strategy analysis of HDM-4 has been presented for low-volume roads (Veeraragavan & Reddy 2003). The relationship between optimal pavement design and maintenance strategy and the level of economic development (LED) were investigated using HDM-4 (Tsunokawa & Ul-Islam, 2003). The 'Project Analysis' and 'Programme Analysis' applications of HDM-4 has been used to develop the Pavement Maintenance System (PMS) for Indian National highways after due calibration of the deterioration models (Aggarwal et al. 2004 & Jain el al. 2004). The HDM-4 tool was also applied after due calibration to develop maintenance plan for the Washington State Department of Transportation's (WSDOT's) road network (Li et al. 2005) and for Iran (Fakhri & Rooeinbakht 2004). A web-based tool for The Western Cape Provincial Administration (WCPA) in South Africa was developed that allowed a user to obtain an HDM4 Version 2 workspace that is to be used in the LCCA (Burger & Gryp 2008). Strategic analysis application of HDM-4 was adapted to derive optimal capital and recurrent maintenance needs to

clear existing maintenance backlogs and thereafter keep the local road network of UK in good condition on a sustainable basis (Odoki et al. 2012). The prioritization of pavement sections for maintenance, a key component of PMS, can be done using HDM-4 on the basis of Net Present Value by Agency Capital Cost (NPV/CAP) value (Shah et al 2014).

4. Objectives of the study

The main objectives of this study are:

i. To apply HDM-4 strategic analysis to a network of selected urban roads of Noida City, and

ii. To determine the required funding levels for the defined maintenance and improvement standards on the basis of two criteria: (i) maximizing the NPV and (ii) minimization of the costs to achieve target international roughness index (IRI).

5. Illustrations

NOIDA city is considered to be one of the most modern cities of Uttar Pradesh state of India, located about 20-kilometre southeast of New Delhi. The study area included 21 urban pavement sections, constituting a total length of 60 km of NOIDA city. The details of these road sections are given in Table 1.

Table 1. Details of selected urban road sections.

Sr. No. Name of the Road Section ID Length (km)

1 Noida Link Road UR 01 3.8

2 Jamnalal Bajaj Marg (MP Road No 1) UR 02 3.5

3 Maharaja Agrasen Marg & Ashok Marg (MP Road No 2) UR 03 6.0

4 Amrapali Marg & Golf Marg (MP Road No 3) UR 04 7.5

5 Udhyog Marg UR 05 3.2

6 Vindayachal Marg & Shivalik Marg UR 06 2.2

7 Nithari Road UR 07 2.4

8 Kamal Marg UR 08 3.0

9 Khoda Village Road UR 09 2.2

10 Sector - 62 Road Along NH-24 UR 10 2.0

11 Sector - 62 Road (Rajat Vihar to Mamura crossing) UR 11 3.3

12 Kakral Road (60M) (Phase - II) UR 12 1.8

13 Mahamaya Balika Inter college Road (60M) UR 13 4.0

14 Panchsheel Bal Inter College Road (45M) UR 14 2.3

15 45M Peripheral Road in Sector - 88 UR 15 2.5

16 24M Road in Sector - 88 UR 16 3.0

17 Amity University Road (Between Sector 125 & 126) UR 17 0.7

18 Lotus Valley Inter School Road (Between Sector 126 &127) UR 18 0.7

19 Road along NGN Expressway (45M) (Connecting Sector 126 & 127) UR 19 2.0

20 Harsing Nagar Marg UR 20 3.2

21 Road between Sector 7 & 8 (Near Vasundhara Enclave) UR 21 0.7

Note: MP - Master Plan; DSC -Dadri-Surajpur-Chalera; NITHE -National Institute of Training of Highway Engineers; NGN - Noida Greater Noida.

Data collection for all pavement sections was aimed to meet the requirements of HDM-4 input system. The process of data collection was classified under following three categories:

(i) Road Network Data: The road network data collection in the field included road Inventory data and road geometric details, structural evaluation (structural capacity), functional evaluation (pavement condition and riding quality) and evaluation of pavement material. The characteristics of selected road sections are presented in Table 2.

(ii) Vehicle Fleet Data: The vehicle fleet data included the collection of basic vehicle characteristics, economic cost details of vehicles and traffic volume count & growth factors. The vehicle fleet characteristics are presented in Table 3 for motorized vehicles and in Table 4 for non motorized vehicles considered in this study. Table 5 presents the economic cost details for the selected vehicle categories.

Maintenance and Rehabilitation Works History: This includes collecting the information about current surface thickness (mm) & Base thickness (mm), last reconstruction or new construction year, and last rehabilitation/resurfacing/preventive treatment year.

Table 2. Road network data.

Section ID Length (km) Carriageway Width (m) Current Surface Thickness (mm) Last Resurfacing/ Strengthening Year Pavement Type MT AADT NMT AADT DCTS (mm) Roughness (IRI m/km)

UR 01 3.8 10.5 40.0 2006-07 AMAP 54476 1602 1.354 3.43

UR 02 3.5 10.5 40.0 2006-07 AMAP 35807 3073 1.435 5.16

UR 03 6.0 10.5 40.0 2008-09 AMAP 35707 5073 1.563 3.41

UR 04 7.5 10.5 50.0 2008-09 2009-10 AMAP 33381 1587 1.298 4.89

UR 05 3.2 10.5 40.0 2002-03 AMAP 24912 1707 1.342 4.85

UR 06 2.2 10.5 50.0 -- AMAP 20332 3814 1.287 4.77

UR 07 2.4 10.5 40.0 2008-09 AMAP 16804 3924 1.189 3.21

UR 08 3.0 10.5 40.0 2009-10 AMAP 19930 3709 1.989 5.65

UR 09 2.2 10.5 40.0 2006-07 AMAP 18450 4178 1.231 4.39

UR 10 2.0 10.5 40.0 2006-07 AMAP 10637 982 1.42 4.45

UR 11 3.3 7.0 50.0 2007 AMAP 12686 3960 2.378 4.67

UR 12 1.8 10.5 40.0 2006-07 AMAP 7961 1523 1.543 4.57

UR 13 4.0 10.5 40.0 2008-09 AMAP 2290 252 2.453 3.57

UR 14 2.3 10.5 40.0 2008-09 AMAP 6114 538 2.533 3.89

UR 15 2.5 10.5 40.0 2005-06 AMAP 1324 302 2.873 4.67

UR 16 3.0 7.0 40.0 2005-06 AMAP 3660 631 2.313 3.98

UR 17 0.7 7.0 50.0 2005-06 AMAP 3279 415 1.724 5.27

UR 18 0.7 7.0 40.0 2005-06 AMAP 6066 893 1.597 5.39

UR 19 2.0 10.5 40.0 2005-06 AMAP 3373 367 1.783 4.86

UR 20 3.2 10.5 40.0 2008 AMAP 18645 3423 1.829 3.87

UR 21 0.7 7.0 40.0 2006-07 AMAP 7286 3697 1.872 4.69

Note: IRI- International Roughness Index, MT-Motorized Traffic, NMT- Non Motorized Traffic, AADT-Annual Average Daily Traffic, AMAP - Asphaltic Mix on Asphaltic Pavement, DCTS - Characteristic Deflection

Table 3. Motorized vehicle fleet basic details.

Motorized Vehicle Category

Description Scooter / M.C. Car/Jeep / Van Mini bus Bus Mini Truck Truck Tractor Trolley Auto

PCSE 0.5 1 1.2 1.8 1.5 1.8 2.2 1

No. of wheels 2 4 4 6 4 6 4 3

No. of Axles 2 2 2 2 2 2 3 2

Tyre Type Radial Ply Radial Ply Radial Ply Radial Ply Radial Ply Radial Ply Radial Ply Radial Ply

Annual km 10000 30000 60000 85000 50000 90000 8000 35000

Annual Works 500 600 3000 4000 2200 3000 500 800

Avg. Life (Years) 8 10 8 11 10 12 8 7

Private Use (%) 100 90 0 0 0 0 0 0

Passengers 1 3 20 50 0 0 0 3

Work related Trips (%) 75 75 75 75 0 0 0 75

ESALF 0 0 0.25 1.7 1.7 2.5 1.4 0

Oper. Weight in Tonnes 0.2 1.35 4 9 4 14 6 1

Note: M.C. - Motor Cycle, PCSE - Passenger Car Space Equivalency Table 4. Non-motorized vehicle fleet basic details.

Description

Vehicle

Category

Wheel Type No. of wheels Wheel Diameter (m) Passen-gers Works Hour Annual km Avg. Life (Years) Pay Load (kg) Oper. Weight (kg)

Pneumatic 2 0.7 1 150 2500 8 35 80

Pneumatic 3 0.7 3 500 6000 6 235 250

Bicycle Cycle Rickshaw

Table 5. Road user economic cost data for representative vehicles.

Description

Scooter /M.C.

Car/Jeep /Van

Mini bus

Motorized Vehicle Category (Cost in Rs.)

Tractor/

Mini Truck

Trolley

Auto Bicycle Ricksh

Purchase Cost (New Veh.)

Replace Tyre (per No.) Fuel

(per litre) Lubr. Oil (per litre) Maint. Labour (per hr) Crew Wages (per h)

Passenger Work Time (per h)

Passenger Non-work time (per hr)

Cargo Holding (per h)

500 70 250 15 0

500000 1000000 2000000 1200000 1500000

1600000 200000

2000 70 280 15 20

5000 50 280 20 80

7000 50 280 30 80

7000 50 280 20 80

7000 50 280 30 80

7000 50 280 20 50

1000 50 280 15 30

100 0 0 0 0

100 0 0 0 20

6. 'Strategy Analysis' Application of HDM-4

Considering the prevailing maintenance strategies, various maintenance and rehabilitation (M&R) alternatives proposed for this study with their intervention criteria's are given in Table 6. The 21 representative sections are analyzed for the investment alternatives given in Table 6. The routine maintenance has been considered as a base alternative for the analysis. The total damage area, which comprise of total area of cracking, raveling and pothole has been considered to be the primary controlling factor for activating resealing of pavement surface. Roughness has

been considered to be the primary controlling factor for activating provision of overlays and strengthening of the pavement.

Table 6. Proposed M&R strategies and intervention criteria.

Work Standard / Intervention Level

Sr. No. Alternatives Type of Maintenance Description of Work For Arterial Roads For Sub arterial Roads

Crack Sealing > 5 % > 10 %

1 Base Alternative Routine Maintenance Patching Pothole Repair Ravel Repair Side Drain Cleaning > 5 % > 1 No. > 5 % Scheduled annually > 10 % > 3 No. > 10 % Scheduled annually

2 Alternative 1 Resealing 25 mm SBSD Total damage area > 5% of total area Total damage area > 10% of total area

3 Alternative 2 Thin Overlay Overlay 25 mm SDBC Roughness > 2.8 m/km IRI Roughness > 4 m/km IRI

4 Alternative 3 Thick Overlay Overlay 40 mm BC Roughness > 2.8 m/km IRI Roughness > 4 m/km IRI

5 Alternative 4 Resealing + Overlay 25 mm SBSD + Overlay 40 mm BC Total damage area > 5% of total area, and Roughness > 2.8 m/km IRI Total damage area > 10% of total area, and Roughness > 4 m/km IRI

6 Alternative 5 Strengthening 50 mm DBM + 40 mm BC Roughness > 5 m/km IRI and Carriageway cracked Roughness > 6 m/km IRI and Carriageway cracked

area > 10% of total area area > 15% of total area

Note: IRI - International Roughness Index, SBSD - Single Bituminous Surface Dressing, SDBC - Semi Dense Bituminous Concrete, BC -Bituminous Concrete, DBM - Dense Graded Bituminous Macadam

The strategic analysis has been carried out for the selected urban road network. The analysis is carried out to maximize the NPV or minimize the costs to achieve a desirable target IRI, which means the maximum IRI at or below which the network is to be kept. The project period has been considered to commence from the year 2014. The economic analysis has been carried out for a design period of 10 years considering a discount rate of 12%. The analysis has been done using the M&R standards same as that used for LCCA.

6.1. Maximize NPV

On analyzing the sections under strategy analysis to maximize the NPV, an unconstrained work program has been generated through HDM-4. Table 7 shows the results of the strategy analysis to maximize NPV with the total cumulative cost for maintenance and the alternatives with the highest NPV. From Table 7 it is seen that the investment alternative that maximizes the NPV for sections UR 09, UR 10, UR 13, UR 17 & UR 19 is 'Thin Overlay of 25 mm SDBC' and for section UR 06 & UR 20 is 'Thick Overlay of 40 mm BC'. For r emaining 13 sections the 'Strengthening with 50 mm DBM + 40 mm BC' was the one that maximizes the NPV. The total capital cost required has been estimated as Rs. 643.96 million.

Table 7. Unconstrained work programme of strategy analysis considering maximizing NPV.

Section Length (KM) Year Work Description NPV/ CAP Financial Cost Cumulative Cost

UR 01 3.80 2014 Strengthening 12.28 29.89 29.89

3.80 2021 Strengthening 12.28 29.89 59.77

UR 02 3.50 2014 Strengthening 16.53 27.53 87.30

3.50 2021 Strengthening 16.53 27.53 114.82

UR 03 6.00 2014 Strengthening 18.67 47.19 162.01

6.00 2021 Strengthening 18.67 47.19 209.20

UR 04 7.50 2014 Strengthening 17.76 58.98 268.18

7.50 2021 Strengthening 17.76 58.98 327.16

UR 05 3.20 2014 Strengthening 17.15 16.78 343.94

3.20 2022 Strengthening 17.15 16.78 360.72

UR 06 2.20 2014 Thick Overlay 11.50 8.27 368.99

2.20 2015 Thick Overlay 11.50 8.27 377.26

2.20 2020 Thick Overlay 11.50 8.27 385.53

UR 07 2.40 2014 Strengthening 6.17 18.87 404.40

UR 08 3.00 2014 Strengthening 16.70 23.59 428.00

3.00 2021 Strengthening 16.70 23.59 451.59

UR 09 2.20 2014 Thin Overlay 9.16 5.15 456.74

2.20 2015 Thin Overlay 9.16 5.15 461.89

2.20 2018 Thin Overlay 9.16 5.15 467.04

2.20 2022 Thin Overlay 9.16 5.15 472.19

UR 10 2.00 2014 Thin Overlay 4.75 4.68 476.88

2.00 2015 Thin Overlay 4.75 4.68 481.56

2.00 2017 Thin Overlay 4.75 4.68 486.24

2.00 2020 Thin Overlay 4.75 4.68 490.93

UR 11 3.30 2014 Strengthening 41.45 17.30 508.23

UR 12 1.80 2014 Strengthening 3.65 14.16 522.38

UR 13 4.00 2014 Thin Overlay 0.26 9.37 531.75

4.00 2017 Thin Overlay 0.26 9.37 541.12

4.00 2021 Thin Overlay 0.26 9.37 550.48

UR 14 2.30 2014 Strengthening 2.62 18.09 568.57

UR 16 3.00 2014 Strengthening 3.34 15.73 584.30

UR 17 0.70 2014 Thin Overlay 5.43 1.09 585.39

0.70 2015 Thin Overlay 5.43 1.09 586.49

UR 18 0.70 2014 Strengthening 7.34 3.67 590.16

UR 19 2.00 2014 Thin Overlay 1.56 4.68 594.84

2.00 2015 Thin Overlay 1.56 4.68 599.52

2.00 2019 Thin Overlay 1.56 4.68 604.20

UR 20 3.20 2014 Thick Overlay 11.52 12.03 616.23

3.20 2016 Thick Overlay 11.52 12.03 628.26

3.20 2020 Thick Overlay 11.52 12.03 640.29

UR 21 0.70 2014 Strengthening 12.37 3.67 643.96

All costs are expressed in Million Indian Rupees NOTE: i. Thin overlay = 25 mm SDBC, ii. Thick overlay = 40 mm BC, iii. Strengthening = 50 mm DBM + 40 mm BC

6.2. Minimization of costs to achieve target IRI

On analyzing the urban road network with the criteria of minimizing costs for a target IRI, HDM-4 produced a constrained program as given in Table 8. From Table 8 it is seen that for all 21 sections, the 'Strengthening with 50 mm DBM + 40 mm BC' is the best investment alternative because it keeps the entire road network at an acceptable condition, as shown in Figure 1. The total capital cost for this option is estimated as Rs. 720.91 million.

Table 8. Constrained program to minimize costs for target IRI.

Section Length (KM) Year Work Description NPV/ CAP Financial Cost Cumulative Cost

UR 01 3.80 2014 Strengthening 12.28 29.89 29.89

3.80 2021 Strengthening 12.28 29.89 59.77

UR 02 3.50 2014 Strengthening 16.53 27.53 87.30

3.50 2021 Strengthening 16.53 27.53 114.82

UR 03 6.00 2014 Strengthening 18.67 47.19 162.01

6.00 2021 Strengthening 18.67 47.19 209.20

UR 04 7.50 2014 Strengthening 17.76 58.98 268.18

7.50 2021 Strengthening 17.76 58.98 327.16

UR 05 3.20 2014 Strengthening 17.15 16.78 343.94

3.20 2022 Strengthening 17.15 16.78 360.72

UR 06 2.20 2014 Strengthening 8.24 17.30 378.02

2.20 2023 Strengthening 8.24 17.30 395.32

UR 07 2.40 2014 Strengthening 6.17 18.87 414.20

UR 08 3.00 2014 Strengthening 16.70 23.59 437.79

3.00 2021 Strengthening 16.70 23.59 461.38

UR 09 2.20 2014 Strengthening 5.42 17.30 478.69

2.20 2023 Strengthening 5.42 17.30 495.99

UR 10 2.00 2014 Strengthening 2.62 15.73 511.72

2.00 2023 Strengthening 2.62 15.73 527.45

UR 11 3.30 2014 Strengthening 41.45 17.30 544.75

UR 12 1.80 2014 Strengthening 3.65 14.16 558.90

UR 13 4.00 2014 Strengthening 0.15 31.46 590.36

UR 14 2.30 2014 Strengthening 2.62 18.09 608.45

UR 15 2.50 2014 Strengthening 0.06 19.66 628.11

UR 16 3.00 2014 Strengthening 3.34 15.73 643.84

UR 17 0.70 2014 Strengthening 3.13 3.67 647.51

UR 18 0.70 2014 Strengthening 7.34 3.67 651.18

UR 19 2.00 2014 Strengthening 1.34 15.73 666.91

UR 20 3.20 2014 Strengthening 8.19 25.17 692.08

3.20 2023 Strengthening 8.19 25.17 717.24

UR 21 0.70 2014 Strengthening 12.37 3.67 720.91

All costs are expressed in Million Indian Rupees

NOTE: Strengthening = 50 mm DBM + 40 mm BC

S 8 js

■Base Alternative

Resealing

Resealing & Overlay

■ Strengthening

■ Thick Overlay Thin Overlay

2014 2015 2016 2017 2018 2019 2020 2021 2022 2023

Fig. 1. Average IRI for urban road network under strategy analysis.

7. Conclusions

The selection of the best maintenance alternative and forecasting the maintenance budget requirement for a selected road network depend on the criteria that a planner adopts. The planning criteria may be maximizing the NPV or keeping the average road network in an acceptable condition. The following conclusions have been drawn from the analysis:

- When the criterion of maximizing NPV has been used, the 'Thin Overlay of 25 mm SDBC' maintenance results in maximum (NPV) for sections UR 09, UR 10, UR 13, UR 17 & UR 19 and for section UR 06 & UR 20 is 'Thick Overlay of 40 mm BC'. For remaining 13 sections the 'Strengthening with 50 mm DBM + 40 mm BC' was the one that maximizes the NPV.

- When the criterion of minimizing costs for target IRI was considered, the ' Strengthening with 50 mm DBM + 40 mm BC' is the best investment alternative because it keeps the entire road network at an acceptable condition.

The HDM-4 strategic analysis can serve as a customized economic evaluation tool in forecasting budget requirements and network condition and can be used for managing urban roads on the basis of sound engineering principles.

References

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. Battiato, G., Ame, E. and Wagner, T., 1994. Description and implementation of RO.MA. for urban road and highway network maintenance.

Proceeding of 3rd International conference on Managing Pavements, San Antonio, Texas. Burger, A.F. and Gryp, A. V.D., 2008. Implementing HDM-4 Version 2 for project level life cycle cost analysis. Proceedings of 7th International

Conference on Managing Pavement Assets, Alberta, Canada. Chen, X., Dossey, T., Hudson, W.R., 1994. Development of project-level urban roadway management system. Transportation Research Record

No.1455, Transportation Research Board, 62-68. Fakhri M. and Rooeinbakht, F., 2004. Application of HDM-4 as a road management system in Iran. Proceedins of 6th International Conference on

Managing Pavements, Brisbane, Australia. Jain, S.S., Aggarwal, S. and Parida, M., 2004. HDM-4 pavement deterioration models for Indian national highway network. Journal of Transportation Engineering, 131(8), 2005, pp. 623-631.

Li, J., Muench, S. T., Mahoney, J. P., Sivaneswaran, N., Pierce, L. M. and White, G. C., 2005. The highway development and management system in Washington state: calibration and application for the department of transportation road network. Transportation Research Record No. 1933, Transportation Research Board, 53-61. Odoki, J. B., Anyala. M. and Bunting, E., 2012. HDM-4 adaptation for strategic analysis of UK local roads. Proceedings of the ICE - Transport,

166(2), 65 -78.

Shah, Y.U., Jain, S.S. and Parida, M., 2014. Evaluation of prioritization methods for effective pavement maintenance of urban roads.

International Journal of Pavement Engineering, 15(3), 238-250. Sohail, F. and Hudson, W.R., 1996. Network-level implementation of URMS: A graphical urban roadway management system. Transportation

Research Record No.1524, Transportation Research Board, 36-47. Tsunokawa, K. and Ul-Islam, R., 2003. Optimal pavement design and maintenance strategy for developing countries: an analysis using HDM-4.

International Journal of Pavement Engineering, 4(4), 193-208. Veeraragavan, A. and Reddy, K. B. R., 2003. Application of highway development and management tool for low-volume roads. Transportation Research Record No. 1819, Transportation Research Board, 24-29.