PRIORITIZATION OF MAINTENANCE MANAGEMENT DECISIONS FOR URBAN TRANSPORT NETWORK

Abstract

Road infrastructure development is one of the major sectors contributing to the National economy. Maintaining these roads is one of the most important component of the entire road system and should not be neglected, particularly in developing countries like India where paradoxically, it is needed the most. The magnitude of work involved in maintenance is very large but the funds available are not enough to meet the requirements. The shortfall for maintenance funds is around 40%. As per Vision 2021-IRC report, the total replacement cost of the existing network is assessed to be about Rs 500,000 crore. So these are huge national assets and maintenance of these roads is an economic necessity. This creates the need to develop a comprehensive pavement maintenance decision support system which can suggest the optimum maintenance actions required and prioritize the highway sections based on available funds. 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. Among these, inadequate drainage is most responsible for the failure of city roads as there is no natural drainage in case of urban roads. 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 thesis proposes a system consisting of six modules for the prioritization of maintenance management decisions for the identified urban transport network. These modules are (i) data collection module (ii) pavement condition evaluation module, (iii) urban pavement maintenance management system (UPMMS) module, (iv) urban pavement drainage management system module (v) maintenance priority ranking module, (vi) Geographical Information System (GIS) integrated with UPMMS module. Looking to the increasing rate of industrialization and urbanization, Noida city has been selected as a study area. NOIDA is one of the largest planned residential and industrial townships of Asia, and it symbolizes harmony between human habitat iv and industrial enterprise in India. It is also a part of the National Capital Region (NCR) and is a suburb of Delhi, capital of India. The first module deals with the collection of data as required for the development of UPMMS. The data collection has been divided into two parts viz. (i) Primary data, and (ii) Secondary data. The primary data included all the details like road inventory, pavement structural & functional condition, evaluation of pavement materials, assessment of drainage conditions, traffic volume and geometric details of the selected urban road network of Noida. The secondary data included population & socio-economic details of study area, maps & layouts of study area, pavement construction and maintenance and rehabilitation (M&R) works history, vehicle fleet data in study area and cost data for M&R activities. These details have been collected from sources like Noida Development Authority, Noida Master Plan 2021, the relevant publications of the Indian Roads Congress (IRC) and the Ministry of Road Transport & Highways (MORT&H), Government of India. The second module evaluates the present distress conditions of individual urban road sections of the study area. In this module, the selected sections have been prioritized for maintenance on the basis of urban road maintenance priority index (URMPI) formulated in the study. The multiple regression analysis and artificial neural network (ANN) techniques have been used to model present serviceability index (PSI) for selected urban roads based on AASHTO guidelines. The relationship between present serviceability rating (PSR) and roughness in terms of international roughness index (IRI) has been developed for the identified network. An overall pavement condition index (OPCI) for individual urban road section has also been computed based on four performance indices viz. pavement condition distress index (PCIDistress), pavement condition roughness index (PCIRoughness), pavement condition structural capacity index (PCIStructure) and pavement condition skid resistance index (PCISkid The third module describes the development of UPMMS for the identified highway sections of Noida using Highway Development and Management (HDM-4) software which is worldwide recognized and accepted tool. Before adopting the HDM-4 tool for analysis all the data has been created in the required format of HDM-4 and files named as ‘Urban Roads Network: Noida’ and ‘Urban Roads Vehicle Fleet: Noida’ has been created. Also, the pavement deterioration models incorporated in the HDM-4 have been calibrated for the local conditions and validated. The ). The M&R strategies have been suggested for each urban road section based the OPCI values. v calibrated model has then been used for the perdition of future pavement conditions. After due calibration, the UPMMS has been developed at project level and network level for the selected urban transport network. The project level analysis included determination of optimum M&R, comparison of scheduled and condition responsive maintenance strategy and estimating remaining service life (RSL) of urban road sections. The optimum maintenance strategies have been determined based on highest NPV/Cost ratio. The ‘Project Analysis’ application module of HDM-4 has been used for performing the project level analysis. The network analysis included life cycle-cost analysis of urban road network giving an unconstrained budget works programme, optimization of resource (budget) allocation for maintenance giving constrained works programme and prioritization of urban road sections for maintenance on the basis of decreasing NPV/Cost ratio. Sensitivity analysis like effect of budget reduction, effect of deferred maintenance and effect of maintenance at different serviceability on the urban road network performance have also been done under network analysis. The ‘Programme Analysis’ application module of HDM-4 has been used for performing the network level analysis. The selected urban road network has also been analyzed under ‘maximize NPV’ and ‘minimize cost to achieve target IRI’ criteria’s using ‘strategy analysis’ component of HDM-4. The fourth module presents the urban pavement drainage management system. This includes (a) evaluation of existing urban pavement drainage condition, and (b) suggesting the remedial measures for the improvement. The analysis in this module has been divided into four parts such as (i) evaluation of urban pavement surface drainage system, (ii) evaluation of urban pavement sub-surface drainage system, (iii) evaluating the effect of urban drainage quality on pavement performance, and (iv) evaluating the effect of side drains on pavement performance and pavement strength. The programs like ‘PAVDRN’ (Pavement Drainage) and ‘DRIP’ (Drainage Requirements in Pavements) have been used for the analysis of surface and sub-surface drainage system respectively. The effect of urban drainage quality on pavement surface performance has been analyzed under different pavement age, traffic growth rate and saturation time. The pavement surface roughness has been considered as a performance parameter for the analysis. The effect of deterioration and maintenance of side drains on the pavement strength and pavement performance has been evaluated using HDM-4 tool. The fifth module illustrated the use of Analytical Hierarchy Process (AHP) for the priority ranking of the urban road sections for maintenance needs. A rational approach has been proposed in the study to determine the priority of urban road sections considering parameters/factors like vi pavement serviceability rating, road class, riding quality, safety conditions, traffic volume, drainage conditions, importance to community and structural adequacy. The various factors and sub-factors affecting the priority ranking have been arranged in a hierarchical structure. The relative importance of each parameter has been determined through a questionnaire survey. The collected data has been checked for reliability and repeatability using SPSS software. The pair wise comparison matrix has been prepared and evaluated for checking inconsistencies using Expert Choice software. The final weight factors have been estimated for each parameter as per experts’ opinion. Finally an urban priority index (UPI) has been calculated using these weightage for each urban road section and are prioritized for maintenance considering higher the UPI, higher the priority. A comparison has been also made between the prioritization of various maintenance activities obtained from URMPI, HDM-4 and AHP method for all 21 urban road sections. The URMPI and AHP methods are based on subjective rating where as HDM-4 is based on objective judgement. Therefore, the priority rankings are not exactly meeting through analysis process but accurate judgments will precise more equality. The principal objective of sixth module is to reveal the role of the GIS technology in the enhancement of UPMMS. A variety of spatially integrated data are important to pavement management decision making. GIS technology is shown to be the most logical way of relating these diverse, but relevant, data. Looking at the UPMMS process in its entirety leads to the enumeration of a set of functions to be embedded in the GIS platform that is required for effective GIS-UPMMS. These functions include thematic mapping, a flexible data base editor, formula editing, statistics, charting, network generation and integrating to external procedures. As a part of formulation of GIS-UPMMS, the output results from the second, third & fifth module have been made more interpretable through sophisticated visualization techniques than the conventional tabular data format. Altogether a concise and succinct approach for pavement maintenance and management have been developed using ArcGIS in hand with UPMMS. Thus, the thesis presents a simplified and a scientific approach for prioritization of maintenance management decisions for urban transport network. The suggested approach could be adopted for development of UPMMS for other cities in India as well as other developing countries having similar conditions. This study would be beneficial to the municipal corporations and urban development authorities in planning urban road maintenance strategies in a systematic manner and to ensure rational utilization of limited maintenance funds.