Draft:National Rail Plan (India)

No

The National Rail Plan (NRP) is a proposal by the Indian Railways to create a ‘future ready’ railway system in India by 2030. The primary objective of the plan is to create capacity ahead of demand, which in turn would also cater to future growth in demand right up to 2050 and also increase the modal share of railways to 45% in freight traffic and to continue to sustain it.

Objectives
The key objectives of the National Rail Plan are :-

58 super-critical projects of a total length of 3750 km costing ₹39,663 Crore and 68 critical Projects of a total length of 6913 km costing ₹75,736 Crore, have been identified for completion by 2024.
 * Formulate strategies based on both operational capacities and commercial policy initiatives to increase modal share of the Railways in freight to 45%.
 * Reduce transit time of freight substantially by increasing average speed of freight trains to 50 km/h.
 * As part of the National Rail Plan, Vision 2024 has been launched for accelerated implementation of certain critical projects by 2024 such as 100% electrification, multi-tracking of congested routes, upgradation of speed to 160 km/h on Delhi-Howrah and Delhi-Mumbai routes, upgradation of speed to 130 km/h on all other Golden Quadrilateral-Golden Diagonal (GQ/GD) routes and elimination of all Level Crossings on all GQ/GD route.
 * Identify new Dedicated Freight Corridors.
 * Identify new High Speed Rail Corridors.
 * Assess rolling stock requirement for passenger traffic as well as wagon requirement for freight.
 * Assess locomotive requirement to meet twin objectives of 100% electrification (Green Energy) and increasing freight modal share.
 * Assess the total investment in capital that would be required along with a periodical break up.
 * Sustained involvement of the Private Sector in areas like operations and ownership of rolling stock, development of freight and passenger terminals, development/operations of track infrastructure etc.

Background
With a vision to develop Indian Railways as a world class system which shall be able to cater to the demand by keeping pace with growth and compliment the economic development, the Ministry of Railways envisioned the preparation of National Rail Plan (NRP) for India keeping the year 2050 as the horizon. For this purpose, the ministry mandated the Rail India Techno Economic Services (RITES) to provide advisory services by further appointing a consultant. In pursuance of the above and to enable preparation of National Rail Plan, RITES assigned the study to M/s AECOM India Private Limited. AECOM commenced the study in January 2019.

The study commenced with having the base year as 2019 and the horizon year as 2050. As a part of the final report the below reports were delivered :


 * Inception Report including work plan, methodology, schedule, working arrangement etc.
 * Interim Report documenting existing situation, base data collection, base data analysis.
 * Demand Forecast Report comprising of travel demand forecast for both passenger and rail including the share that will be carried by Railways in future.
 * AS-IS Network Mapping comprise of mapping the whole network of Indian Railways as per the existing situation including their respective attributes such as line type, speeds, etc.
 * Future Network Requirement Report shall include the Railway Network Improvement proposals based upon Demand Forecasts of Passengers and Freight.
 * Option Identification and Evaluation Report for Capacity Creation shall include various Railway Infrastructure development Options, their phasing and evaluation in terms of implementation and timelines.
 * Draft Final Report comprising of all the base data analysis, demand forecast, network and infrastructure development proposals, phasing timelines, broad cost estimation and financial analysis.
 * Final Report Incorporating Comments on Draft Final Report.

AS-IS Network Mapping
For the preparation of the NRP, a base map of the network on GIS Platform was prepared. This map has been digitized through ArcGIS to represent the secondary data provided by the Indian Railways on GIS ArcMap through schematic maps. The study area for the NRP AS-IS rail network map covers the entire territory of India with an area of 3.287 million sq. km. The Indian Railways zonal map of 2018 was georeferenced, mosaicked and vectorized. After this, digitization of railway station locations, railway line routes and zonal and divisional boundaries were done.

Utilizing the digitized data, railway connectivity to cities with a census designation of Class I (cities with population greater than 1,00,000) and Class II (cities with population greater than 500,000 but lesser than 1,00,000) along with major tourist places in India were mapped.

Demand Forecast
In order to predict future rail network requirements for passenger and freight rail, demand forecasting was performed for the horizon and cardinal years. Extensive secondary data was collected by AECOM from various sources, including the Ministry of Railways and other Ministries. Data collected from the Passenger Reservation System (PRS) and the Unreserved Ticketing System (UTS) included information such as month, railway zone code, railway division code, train number, station code, station name, distance, class code, passengers, boarding and alighting station, boarding and alighting zone, boarding and alighting division, number of passengers, and concession in rupees. Secondary data collected from the Freight Operation and Information System (FOIS) included details of line capacity charts, IR system maps, permanent speed restrictions, train master details, station name list, and coaching terminals.

Primary data collection involved carrying out various traffic and transportation surveys, including classified traffic volume counts, passenger and goods origin-destination surveys, and freight stakeholders' consultations. These surveys aimed to establish the baseline data for future transport demand and assist in traffic model development. A total of 100 locations were selected for the surveys based on key parameters such as million-plus cities, state capitals, logistics hubs, major cement production centers, agricultural districts, and more. The classified traffic volume count survey was conducted at 104 locations using videography technology for a duration of 24 hours over 7 days. Seasonal correction factors were applied to adjust the data collected from traffic count stations to derive annual average daily traffic (AADT). Passenger and goods origin-destination surveys were conducted along with the classified traffic volume count surveys. The output from these surveys included the travel pattern of vehicles, lead distribution, load distribution, commodity movement pattern, occupancy, and trip purpose. The study area was divided into traffic analysis zones (TAZs) to better understand the travel pattern and interaction with external regions. A total of 701 TAZs were identified, including internal and external zones.

The passenger demand forecast analysis revealed that railway passengers had grown at a compound annual growth rate (CAGR) of 2% per annum. The growth was observed in different passenger categories, with maximum growth in the AC category. Suburban passenger traffic also experienced growth. The composition of passenger traffic across different classes showed that the unreserved class accounted for the majority share (93%) in total rail passenger traffic. Sleeper class and AC class constituted 4% and 2% of the rail passenger share, respectively. The travel pattern of reserved passengers highlighted the busiest routes, such as Bengaluru-Chennai and Chennai-Coimbatore. The analysis also revealed the concentration of reserved passenger trips around metro cities and other major cities. The travel pattern of unreserved passengers showed the Mumbai suburban railway network as the busiest, followed by the Chennai suburban railway network. Significant flows of long-distance unreserved passenger trips were observed from Mumbai and Punjab to various destinations. The analysis based on city size revealed that metropolitan cities accounted for a significant share of reserved passengers, while tier 1 cities and tier 2/3 cities also contributed. Non-urban areas accounted for 9% of total rail passengers.

The road passenger travel characteristics were also analyzed, with the travel pattern and estimated quantum of passenger trips captured through Road Side Interviews (RSI) for origin and destination survey. Metropolitan cities like Bangalore, Chennai, Pune, Hyderabad, and Mumbai constituted a significant share of total regional passenger movements.

Estimation of rail freight share
To determine the share of rail in freight transportation and developing strategies to increase it, analysis of the current and projected share of rail in carrying commodities, taking into account production, demand, and proposed railway projects was performed. It was found that in the year 2017-18, railways were responsible for transporting 1,162 million tonnes, which accounted for 26% of the total freight movement. On the other hand, road transport contributed to 2,911 million tonnes, representing 65% of the total. Over the years, both rail and road freight movement doubled since 2007-08. However, the share of rail in carrying freight beyond 300 km decreased from 51.5% in 2007-08 to 32.4% in 2018-19, primarily due to the limited availability of railway freight wagons.

It was found that when considering different lead ranges, railways carried 38% of freight within a 300 km range and 70% within a 600 km range, while road transport accounted for 48% and 70% respectively. In terms of specific commodities, coal held the largest share in both rail and road freight, followed by Balanced Other Goods (BOG) which were predominantly transported by road. Rail transport had a significant share in transporting fertilizers, pig iron, and iron ore. The average trip length varied across commodities, with food grains having the highest average lead for rail, while petroleum, oil, and lubricants (POL) had the highest average lead for road transport. Future freight projections indicated growth in production and consumption. To estimate rail's share in carrying commodities, a mode choice model considering travel time and cost was utilized. The future Origin-Destination Matrix for freight distribution was prepared using the Fratar Distribution model, which took into account the relative attractiveness and growth of each zone. Various scenarios were considered to estimate rail's future share, factoring in changes in time and cost parameters, including the impact of proposed railway projects.

Freight flow assessment and modal share of railways
The study analyzed the flow of freight and the modal share of railways. It identified 27 commodities and classified them into ten groups, including coal, iron ore, steel, and cement. It was found that the railways were preferred for conventional bulk commodities, while road transport was favoured for high-value and non-conventional goods. Stakeholder consultations and econometric modeling projected future demand for key commodity groups. Through this it was found that the modal share of railways has declined from 50% to around 30% due to factors like changes in industrial patterns and improved road infrastructure. Stakeholders emphasized the need for Indian Railways to enhance its logistics proposition and reduce emissions. The National Transport Development Policy Committee recommended a 50% market share for Indian Railways by 2032. Strategies like market-oriented approaches, technology adoption, and customer-centric initiatives were recommended to increase rail modal share. Indian Railways established business development units and proposed a policy framework to address customer needs and attract freight from logistics service providers. Data-driven solutions and improved connectivity were recommended. It was found that rail pricing for bulk commodities was cost-effective, but for high-value and non-bulk goods, rail loses to road transport. The operationalization of DFCs and pricing initiatives were recommended to help reduce rail logistics costs. IT-driven solutions, integrated systems, and improved terminal networks were marked as essential for efficient rail planning and performance. Targeted logistics solutions based on cargo characteristics were recommended to increase rail modal share in different commodity groups.

Rail network corridor demand
The study analyzed & identified potential demand corridors for passenger and freight transportation. 7 High-Density Network (HDN) routes and 11 Highly Utilized Network (HUN) routes were classified, accounting for a significant portion of the Indian Railway Network and traffic. It was found that while HDN's comprise of 16% (11,000 Km) of the total Indian Railways network, it transported 41% of total traffic of the entire network and while HUN comprise of 35% (24,230 Km) of the total railway network, it transported 40% of the total traffic moving on the Indian Railways network. Together both HDN's and HUN's account for almost 50% (34,214 Km) of the total network while transporting 77% of the total traffic of the entire network.

Passenger Demand Corridors
The demand share of HDN and HUN remained high, indicating the need to augment capacity through additional lines and dedicated corridors.

Freight Demand Corridors
Movement of various freight commodities such as cement, coal, iron ore, containers, fertilizers, steel/pig iron, POL (petroleum, oil and lubricants) and other goods were observed and analyzed across the Indian Railways network and rake matrices of all commodities were added up and then assigned on the rail network for obtaining overall freight demand corridors for each of the cardinal years. The below freight corridors were identified and the major freight corridors where the share of freight traffic was greater than 50% have been further considered for development of Dedicated Freight Corridors (DFCs).

High Speed Railway Corridors
Indian Railways already envisioned developing high-speed railway corridors in India back in 2009 as a part of "Indian Railways Vision 2020”. In the National Infrastructure Pipeline