Abstract

Prioritising highway infrastructure investment schemes is a major problem faced by the road agencies. Often the authorities will have substantial schemes to select from, pressure on resources and public demand for a transparent and consistent ranking process. As transport investments are usually long lasting and costly, decision makers require reliable and logical appraisal methods. A scientific prioritisation methodology to identify the deserving highways for improvement, from an extensive road network serving an entire state is presented here. The method has been evolved by reviewing various literature available in conjunction with the specific project requirements. Multi Criteria Analysis (MCA) approach identified as the most preferred one for the study as it can link highway infrastructure investments to project necessity, economic development, sustainability, compatibility, etc. The content of this paper forms part of the investment proposals recommended for the “State Road Improvement Project, 2012” for a state in India. The objective of the study was to shortlist about 1000kms of roads for improvement from a master list of 4560kms, spread over the entire state which included 84 stretches of state highways (1930 kms) and 280 stretches of major district roads (2630 kms). A two stage approach was employed for the prioritization exercise. The extent of linkages each road stretch offers to the growth centres was considered in the first stage and this exercise resulted in prioritization of about 2500 kms (140 nos.). Stage II focused on finalization of composite index, consisting of seven indices reflecting the importance of the road in the regional network, regional context and environmental and social issues due to the project. A frequency distribution was plotted using the score and the roads with the score above the mean value were selected. Investment schemes were broadly classified into three categories and contiguous road stretches were grouped together to result in seven packages. Economic and financial analysis along with the funding options was recommended for each package.

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