It is estimated that by 2030, 60 percent of the population will be living in urban areas. A necessity for the both the present and future is the efficient movement of large masses of people to and from city centers. The progress of urbanization heavily relies on this. Among various modes of public transportation, railways stand out as the most efficient and effective in terms of energy consumption per passenger kilometer.

However, for rail to be the preferred choice, it needs to be safe, reliability, and available. Currently, digitalization emerges as the most cost-effective means to achieve this. By putting the control of the train in the hands of the digital signalling system, speed and braking are perfectly optimised, allowing you to run more trains safely at faster speeds and shorter intervals. This digital intervention results in increased capacity without increasing capital expenditure, while passengers experience shorter and more dependable journeys. In this way, the benefits of rail digitalisation become global efficiencies.

AI is boosting safety in the railways by minimising risk of human errors

AI is finding significant application in making trains safer. Today, as rail systems are modernizing, automated signalling systems, including driverless train operation, are being adopted with embedded artificial intelligence (AI) to improve safety and efficiency. Equipped with cameras, powered by AI, these systems can capture images and data to identify obstacles that allow operators to take maintenance and corrective action real-time. It can also examine track conditions and notify operators of any safety affecting abnormalities and avert potential derailments.

AI is enhancing passenger and operator experience

The recently inaugurated Namo Bharat has been designed to reduce travel time by 40%, from 100 minutes to 60 minutes, enabling passengers to spend less time, all because of AI, which is being leveraged in train safety, scheduling and speed management. By analysing real-time data, AI algorithms can adjust train schedules to accommodate unforeseen disruptions or changes in passenger demand. This results in reduced waiting time and improved punctuality. It can forecast occupancy levels guiding passengers out of high peaks, give operators higher visibility on passenger distribution and flow in trains and stations, and also help anticipate and control passenger density in real time. This demand-supply matching of trains optimizes operating conditions including costs.

AI is helping operators optimise revenue generation

As estimated, Indian railways was able to achieve an Operating Ratio of 98.14% in FY 23. Indian Railways generates its revenue from freight and passenger service and to maximise gains, it is essential that the trains keep operating. However, to ensure the safety, efficiency and longevity of trains regular maintenance is needed. Though, the downtime for maintenance needs to be kept minimal to maximise on earnings and this is where digital technologies that enable predictive and real time maintenance come handy. AI in railway signalling includes predictive maintenance, where AI analyses data to predict potential failures in rail infrastructure or trains. This allows proactive scheduling of maintenance, reducing downtime and enhancing system reliability. Yet, this comes with its own challenges. These include the need for high-quality, up-to-date data, and ensuring data privacy.

From Automated to Autonomous trains – AI is making trains more self sufficient

AI is playing a significant role when it comes to automation. Autonomous trains offer several benefits, such as improved safety, reduced operating costs, and increased capacity. The combination of systems like Automatic Train Control, Automatic Train Protection and Automatic Train Supervision, these enable operators to do more with less, arranging their fleets and turning them into a finely tuned network that performs better with less waste and risk. Automation expands passenger capacity by increasing the number of trains a line can handle, decreasing the time schedule between two trains to as less as 1 minute. Automating train fleets creates predictability and that predictability enables greater flexibility. Services like maintenance account for a large part of the costs of operating a fleet.

It's clear that AI is playing a pivotal role in modernizing the railways and making them more intelligent, efficient, and sustainable. The railway of the future is a smart network where every aspect of operations is optimized through AI-driven insights. Rail systems offer sustainable mobility with high energy efficiency, capacity to reduce congestion and play a pivotal role in mitigating climate change. Digitalization can help in train control and safety, reduce delays, enhance the passenger experience, and increase capacity, thus contributing to climate mitigation efforts. As AI continues to evolve, even greater innovations in railway technology can be expected, leading to a greener, safer, and more efficient mode of transportation for generations to come.

• Photo by Aleksandr Popov on Unsplash