Project
To ensure the best use of public funds for the maintenance of its road networks, the Odisha Works Department chose to establish a road asset management system for its 14,000-kilometer state road network. The system will help the Odisha Works Department rationalize decision-making in planning, programming, funding, procurement, and allocation of resources. Through the Government of India, the State Government of Odisha received a loan from the International Bank for Reconstruction and Development to implement the Odisha State Roads Project. A portion of this loan was to establish the Odisha Road Asset Management System (O-RAMS).
Solution
The Odisha Works Department collected data for the 14,000 kilometers of roads and 1,300 bridges using GPS-based survey and spatial layer creation, and both automated and manual inventory and condition surveys. The O-RAMS was implemented using Bentley’s AssetWise (formerly called Exor) product which includes the Transportation Intelligence Gateway (TIG) tool.
Outcome
The O-RAMS now provides a vehicle for convincingly demonstrating the region’s road network needs when seeking funds from the federal government. It is also a single source of truth regarding the inventory and condition of Odisha’s roads and bridges. Road asset information is now readily available to approximately 40 offices through a Web browser.
Software
AssetWise provided a ready-to-use proven web-based solution with a number of important features including role based security ensuring that only authorized users are able to create and update road network and asset information; multiple linear referencing capabilities enabling a single road network to be reported and analyzed against using any number of different referencing methods for different business purposes; spatial display of all data; configurable management of all road and bridge information including assets, events, and conditions; and the Bentley Transportation Intelligence Gateway (TIG) tool that provides powerful, dynamic segmentation capabilities and data extraction which is essential to support HDM4 reporting.