Optimising Indian Railways Infrastructure by AI

  • Chandrika Prasad PNCS Rail Consultancy, Former Adl Member Signal Indian Railway Board, Noida, India
  • Sudhanshu S. Jamuar IIIT Delhi, New Delhi, India
Keywords: Indian railway, signalling, artificial intelligence, signal maintenance


The pressure on the Indian railway (IR) networks has increased due to higher demand for mobility and growth in India’s population over past several decades. In order to meet the higher demand,  IR has put priority in capacity building by increasing the number of coaches per train, running more trains, and building more tracks. Building more tracks or increasing the number of coaches or increasing the number of trains have the potential to solve the problem with high infrastructure cost. Unfortunately, it also comes with added vulnerability in safety in running the system. IR with its investment of over 5,00,000 Cr is presently struggling to make its Operating ratio (expenditure / earning) below 100 %. During the last 166 years of its operation, much technological input has been made on its Infrastructure, Locomotives and Rolling stock but its Train Control practices have remained Conventional – locally controlled and experience-based. The developments in the area of signal processing, communication systems, and artificial intelligence (AI) etc. have great potential for applications in Indian Railway right from ticketing to movement of trains, maintenance etc. The potential of AI has been felt in different applications like predicting delays, preventive maintenance of tracks and rolling stocks, forecasting algorithm for the railway systems. The use of AI in the operation of IR will improve performance by using clever algorithms with efficient software and hardware. This in turn will provide lower latency with information sharing and the use of AI in rail operation will surely improve the efficiency in train operation. This paper highlights the potential contributions of AI in improving the operation of India’s railway system and how the application of recent technological advancement in Information Science and Artificial Intelligence can bring a change in the train operation scenario at a railway station and Control Centre and add to the profitability of Indian Railways.


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Author Biographies

Chandrika Prasad, PNCS Rail Consultancy, Former Adl Member Signal Indian Railway Board, Noida, India

Chandrika Prasad is Managing Director of PNCS Rail & Metro Consultancy. He was Additional Member Signal of Indian Railway Board and was responsible for introducing state of art Signaling & Telecom technologies and creating islands of Signaling excellence over Indian Railways. He was Principal Consultant Delhi Metro and Member of UIC Paris ETCS Task Force. He has provided/is providing consultancy for various Railway Projects in India viz. Mumbai – Ahmadabad High Speed, DFCC, RRTS and rail projects in UK, Middle East, Africa, Bangladesh, Myanmar, Shri Lanka etc. He has been Member of several High Level Committee for Railways. Over 32 of his papers have been published/presented in International & National Journals/conferences. For his outstanding contribution to Railway Signaling, he has been conferred with “Honorary Fellow” by Institution of Railway Signal Engineers London and ‘Life Time Achievement Award’ by Institution of Rly Signal & Telecom Engineers India.

Sudhanshu S. Jamuar, IIIT Delhi, New Delhi, India

Sudhanshu S. Jamuar received his Ph. D. in Electrical Engineering from Indian Institute of Technology, Kanpur, India in 1977. From 1968 to 2017, he served in India (IIT Kanpur, IIT Delhi, HAL Lucknow and IIT(ISM) Dhanbad) and in Malaysia (UPM, UM and UNIMAP). He is presently Visiting Faculty at IIIT Delhi. In 1996, he visited Nigeria as UNESCO consultant. He has been teaching and conducting research in the areas of Electronic Circuit Design, Instrumentation and Communication Systems. He is Fellow of IET (UK), Senior member of IEEE and Fellow of Institution of Electronics and Telecommunications Engineering (India) and IET International Professional Registration Advisor. He was DLP speaker for IEEE CAS during 2008–2009. He is on the Editorial Board of Wireless Personnel Communication Journal. He was the Chapter Chair for IEEE CAS in Delhi Section and Malaysia Section from 1999 to 2007. He has published 75 papers in the International Journals and has presented more than 70 papers in International Conferences. He was General Chai for IEEE APCCS 2010 (Malaysia). He has 3 patents and is recipient of IETE Meghnad Saha Memorial 1976, Distinguished Alumni Award from BIT Sindri in 1999, Best paper award in IETE Journal of Education 2004.


Ministry of Railway. Indian Railways Statistical Publications 2016.

Ministry of Railway. Indian Railways Budget Document 2018–19.

Indian Railways general and Subsidiary Rules.

Indian Railways Station Working Rules.

Indian Railways Signal Engineering Manual.

Indian Railways Telecommunication Manual.

G. Raghuram, ‘Turnaround’ of Indian Railways: A Critical Appraisal of Strategies and Processes (PDF), Working Paper No.2007-02-03, Ahmedabad, India: Indian Institute of Management, (February 2007).

G Bocchetti, F Flammini, C Pragliola, and A Pappalardo. Dependable integrated surveillance systems for the physical security of metro railways. In 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC), pages 1–7. IEEE, 2009.

R Borndörfer, M Reuther, T Schlechte, K Waas, and S Weider, Integrated optimization of rolling stock rotations for intercity railways. Transportation Science, 50(3):863–877, 2015.

A Caprara, M Fischetti, P Toth, D Vigo, and P Guida. Algorithms for railway crew management, Mathematical programming, 79(1–3):125–141, 1997.

F Flammini, A Gaglione, F Ottello, A. Pappalardo, C Pragliola, and A Tedesco, Towards wireless sensor networks for railway infrastructure monitoring. In Electrical Systems for Aircraft, Railway and Ship Propulsion, pages 1–6. IEEE, 2010.

H Khadilkar. A scalable reinforcement learning algorithm for scheduling railway lines. IEEE Transactions on Intelligent Transportation Systems, 20(2):727–736,

http://www.indianrail.gov.in, “Indian Railway’s zone’s & their divisions with heaquarters” (pdf), Archived (PDF) from the original on 17 April 2012. Retrieved 23 February 2018.

https://www.linkedin.com/pulse/artificial-intelligence-railway-applications-alexandre-pires-pmp- Alexandre Pires, Artificial Intelligence in Railway Applications.

Derel Wust, Using Machine Learning for Safer and More Efficient Train Operations, NVIDIA GTC 2018, San Jose, CA 2018.

Intelligent Infrastructure for Next-Genration Rail Systems – COGNIZANT 20-20 insights:August 2013.

Mingijia Yin, Kang Li, Xiaoqing Cheng, A review on artificial intelligence in high speed rail, Transpotation Safety and Envioronment, 2020, Vol. 0, No. 0, pp. 1–13 (https://doi.org/10.1093/tse/tdaa022).