I'll See Your Autonomous Vehicle And Raise You An Autonomous Train

By John Oncea, Editor

Autonomous trains are used in various settings, including urban transit systems, metro and subway networks, freight transportation, and high-speed rail. They offer the potential to enhance the reliability and safety of train travel.

A Google search for “autonomous vehicle” brings back thousands of hits. For instance, did you know that  Nvidia is partnering with Mercedes to pursue self-driving cars? Or that Minnesota is part of an autonomous vehicle movement for people with disabilities? And don’t overlook this IEEE article discussing issues surrounding autonomous mobility.

All of this is great. We even cover autonomous vehicles (AVs) ourselves, from their future to the use of 4D imaging radar in autonomous driving to how LiDAR and ADAS are working together to help develop AVs. We looked at legal ramifications and if they’re too annoying, as well.

But you know what’s not in operation today? Yeah, fully automated vehicle.

But you know what is in operation today? Fully autonomous trains. So, with that in mind let’s buy a ticket, head to the platform, and take a ride on an autonomous train!

All Aboard 

Kobe New Transit’s Port Liner, the world’s first automated, unmanned railway opened in Kobe, Japan in 1981, according to Working Japan. Today, there are several additional lines in Japan utilizing unmanned automated driving including Osaka Metro's New Tram, the Yurikamome which runs along Tokyo's waterfront area, the Nippori-Toneri Liner operated by Tokyo Metropolis, the Seaside Line in the southern part of Yokohama City, and the Disney Resort Line connecting Tokyo Disney Resort facilities.

“All of these lines are elevated and their tracks are isolated from ordinary roads,” notes Working Japan. “Doors are installed on the platforms to prevent people from accidentally falling onto the tracks. People and vehicles rarely enter the tracks, there are no railroad crossings where accidents can easily occur, and they are well-protected from flying objects. For this reason, there is a distinctly low level of risk during unmanned driving.”

Automated trains aren’t exclusive to Japan, either – they are operating in more the 40 cities around the world, including Copenhagen, Paris, Singapore, Dubai, and London, according to Allianz Commercial.

The first autonomous train was introduced in the Czech Republic in 2021, and German rail operator Deutsche Bahn and Siemens launched the world's first automated and driverless train in Hamburg the same year. A year later, China unveiled a driverless Fuxing bullet train capable of traveling at speeds of 217 miles per hour in 2022.

Much like the Society of Automotive Engineers (SAE) six levels of driving automation for AVs, the International Association of Public Transport (UITP) has defined four levels of automation for autonomous trains with some trains more autonomous than others. UITP’s Grades of Automation (GoA) range from GoA1 up to GoA4.

• GoA1 is the first Grade of Automation, in which the driver is responsible for all actions, with ATP* supervision.
• In GoA2, traction and braking are performed automatically by ATO*, supervised by ATP. The driver is still present to supervise the doors operation, and operations when disruptions occur.
• In GoA3, there is no driver anymore, but the onboard staff remains present. GoA3 is also called Driverless Train Operation (DTO).
• In GoA4, there is no more staff within the vehicle, and all operations are automated. GoA4 is also called Unattended Train Operation (UTO).

While autonomous driving currently sits at Level 2 on SAE’s scale (partial driving automation), autonomous trains have reached GoA4 (the equivalent of SAE’s Level 5), unattended train operation. According to UITP, “By the end of 2020, there were fully automated metro lines in 48 cities, meaning that more than one in every four metro systems has at least one driverless line.

Alliance Commercial adds, “In the remote Pilbara region of north-western Australia, a heavy-haul locomotive sweeps across the plains, its 240 wagons stretching two and a half kilometers behind it toward the horizon. Laden with iron ore, the driverless train is making the 185-mile journey from mines inland to a port on the Indian Ocean, while a team of controllers from the mining giant Rio Tinto monitors its progress from a control center in Perth, 932 miles away.

 “On the other side of the world in Brazil, the fully automated Line 4 of the Sao Paulo metro system carries a human cargo – sometimes as many as 800,000 people a day – along a seven-mile route through one of the most populous cities on the planet.”

* According to Voie Libre, “ATO stands for Automatic Train Operation, consisting in a set of systems aiming to bring automation into the operations of trains. ATO is coupled with Automatic Train Protection (ATP) to ensure the supervision of the train: the overspeed and trespassing of danger points detection. ATP activates the emergency brake when these events occur.”

Why This Matters

Autonomous trains operate using a variety of sensors, AI-enabled cameras, and machine-learning algorithms to analyze hazards, make decisions, and tell the train what to do. They can operate automatically or with a driver present and help eliminate human error sources, increase capacity, reduce operational costs, increase service reliability and energy efficiency, and improve fleet management and service flexibility. Key features of autonomous trains include:

• Automation Systems: Autonomous trains rely on sophisticated automation systems to control various aspects of train operation, including acceleration, braking, and steering. These systems are designed to ensure safe and efficient train travel.
• Sensors and Cameras: The trains are equipped with a variety of sensors, such as radar, LiDAR, and cameras, to detect obstacles, monitor the track condition, and gather real-time information about the surroundings. These sensors help the train make decisions based on the current environment.
• Communication Systems: Autonomous trains often use advanced communication systems to exchange data with other trains, track infrastructure, and control centers. This communication enables coordinated movement, reduces the risk of collisions, and enhances overall system efficiency.
• Safety Features: Safety is a critical aspect of autonomous train systems. These trains are designed to adhere to strict safety standards and incorporate features like emergency braking systems and fail-safe mechanisms to mitigate risks.
• Efficiency and Precision: Autonomous trains can optimize their speed, acceleration, and deceleration based on real-time conditions. This can lead to improved energy efficiency, reduced travel times, and better overall precision in maintaining schedules.

One of the potential advantages of autonomous trains is the reduction in labor costs associated with train operations. However, the implementation of autonomous technology may also create new jobs related to maintenance, monitoring, and system oversight.

It's worth noting that the deployment of autonomous trains is a complex process that involves thorough testing, regulatory approvals, and the development of comprehensive safety protocols. As technology continues to advance, we may see further adoption of autonomous train systems in different parts of the world.

Brought To You By AI

It should come as no surprise that artificial intelligence (AI) has been instrumental in the evolution of autonomous trains, particularly machine learning and computer vision which can be applied to enable operations. This includes the development of systems that control trains without human intervention, optimizing routes, and responding to real-time conditions.

AI also plays a role in predictive maintenance, analyzing vast amounts of data from sensors and monitoring systems on trains and tracks to predict when components are likely to fail. This enables proactive maintenance, reducing downtime and minimizing disruptions to train services. AI-powered systems are also monitoring the condition of various train components, such as brakes, wheels, and engines in real time, searching for any abnormalities or signs of wear allowing for timely maintenance.

Traffic management and energy efficiency are two operational areas in which autonomous trains benefit from AI when it is used to optimize schedules, manage traffic, and improve overall network efficiency. This helps reduce congestion, enhance punctuality, and maximize the capacity of railway systems. AI is also being used to optimize the energy consumption of trains by analyzing factors such as speed, route, and load. This helps reduce operating costs and environmental impact.

Of course, AI plays a crucial role in developing safety systems for trains including the implementation of collision avoidance technologies, automatic braking systems, and obstacle detection using computer vision. All of this leads to a better passenger experience including the development of smart ticketing systems, personalized services, and real-time information updates for passengers.