The end result of the TAM run is
a commodity wise flow over each section of the Indian Railways. Post processing
of the TAM Output provides a list of bottleneck sections on different routes by
key years. These bottlenecks can be assessed through the user interface and
depicted over the entire network in a bottleneck map. The map above is an output
of the TAM and it depicts the total pattern of flow of traffic in the year
2006-'07. The thickness of the lines is a measure of the density of traffic. Red
part of the network highlights the sections, which are likely to have capacity
problems.
Using this map as the base, the planner can they detail out an
investment
strategy for elimination of these bottlenecks. His strategy
may involve one or all of the following:
- De-market carriage of some commodities
- Enhance the network through a series of actions such as provision of
additional lines, automatic signaling, higher speed locomotives
- Set up and strengthen alternative routes
- Initiate policy changes
The planner may want to generate a series
of scenarios taking these four steps either in sequence or is a simultaneous
manner. Looking at the lead times for various projects, he may opt for
accelerated, normal or decelerated rate of investments.
Each of these
scenarios may involve running of a series of different models in the FPM- e.g.
RAILS Simulation Model-, in the TFM (e.g. Furness Matrix Generator) and MAM
(e.g. Logistics Cost Model) and generation of a series of databases for input
into the TAM. All these tasks can be undertaken through the Avenue User
interface and TAM can be rerun to generate a set of scenario specific output
tables. The impact of different scenarios or projects can then be studied in
detail and annual investment plans made for the Railways as a
whole.
Benefit Cost Analysis (BCA) Module: The Benefit Cost Analysis
Module analyses the impact of alternative scenarios and projects on system wide
costs and benefits. It relates investment costs and investment pattern, project
lead times and changes in operating costs with incremental benefits in the form
of additional or diverted traffic. The results thus obtained can form the basis
of a financial or economic analysis of various investments. The input to the
module is the unit investment costs for various types of works, the traffic
flows as obtained from the TAM and the unit operating costs (i.e. the long-term
line haul variable costs) as generated by the FPM.
The Avenue User
Interface facilitates transfer of TAM output data to Excel. It uses intermediate
Visual FoxPro programs and database files to organize the large amount of TAM
output data. Sensitivity Analysis as well as "With/Without" Analysis of a series
of Investment Projects and their prioritization can be done in the BCAM Excel
Sheets
Financial Forecasting (FF) Module: The Financial Forecasting
Module generates cash flows, expenses and revenues for key years based on the
forecast traffic levels and investment options selected for implementation. It
projects the investment requirements under different plan heads. Additionally,
key year wise Contribution and Financial Statements as well as Sources and Uses
of Funds over a 15- year financial plan can be generated by this module.
ConclusionThe LRDSS has thus emerged as a world class model using GIS
and complex transportation models and data structures, all successfully bundled
into a user-friendly decision support system. It is integrated and
interdisciplinary investment planning tool for planning of complex
transportation systems through a simple and easy to use Geographical Information
System User Interface. Its decision support capability is one of the salient
features that have been built in.
LRDSS is being gradually
institutionalized into the traditional planning process of the Indian Railway
Board. Its use is likely to provide tremendous opportunities for cost reduction
and network optimization within the organization. Use of GIS is likely to
encourage its application in areas such as Asset Management, Property Management
and Customer Response & Prospecting. The LRDSS Model can also be customized
to other infrastructure areas such as Roads, Telecom and Power
Distribution.
(Mr. Bharat Salhotra is a Mechanical Engineer and an MBA
from IIM, Calcutta. He is currently working as Joint Director in the Planning
Directorate of the Indian Railway Board)
Database integrity is a question
mark and a lot of work had to be done to ensure that there is no data loss while
moving the data from one platform /database to another one.
Indian
Railways Network Database: This contains various attributes of the railway
network. Important stations and sections of the network have been encoded on a
map using a Geographical Information System called Arcview. The network is
corrected upto 31.3.97. A future network for 2001-02 has also been prepared on
the basis of anticipated completion of works of new line, electrification and
gauge conversion etc
Traffic Database: An Origin Destination flow table
has been set up for different commodities. This data will be updated annually so
that the latest information on annual flows between pairs of points is available
by commodity. A commodity wise forecast table has been set up containing the
total traffic demand between pairs of points, that is likely to materialize by
the year 2001-'02.
Finance & Cost Database: A list of committed works
alongwith their expected date of completion and the approximated cost has been
entered in a database. Further, a Unit investment cost database for Civil,
Mechanical, Electrical and Signaling works has been set up to enable the user to
build up total project investment costs for different line capacity projects. A
Long-Term Variable Cost database has been created to enable the user to assess
costs per net ton kilometer at different congestion levels for different
commodities.
Facility Performance Database: We have aggregated division
wise data relating to various aspects and features of operation. This data
contains details of interchange points, type and number of trains running on
important sections of that division, ruling gradients, commodities carried, type
of stock used etc. In addition, detailed data of seventeen important links over
Indian Railways such as Sonnagar Mughalsarai, Gomoh Gujhandi, Baroda Surat has
been entered for Simulation Modeling. Output analysis related to congestion,
failure analysis and impact of different technologies can be obtained for these
sections.
ConclusionThe LRDSS will be able to provide the
users with an easy to use information-based tool that can be used for long term
planning over the Indian Railways. A user-friendly interface has been developed
so that the various types of analysis can be done without much
difficulty.
The basic problem has been to attach large transportation
model system to the ArvView. The problem was circumvented by development of a
Avenue based Interface. Need to have a more open and more powerful GIS Arcview
to facilitate attachment of Transportation Models at the back.