Autonomous Trains Make Tracks for Expansion of Connected Mobility

Autonomous Trains

Plans for autonomous trains and the connected artificial intelligence (AI) systems to operate them are getting ready to leave the station — if they haven’t already — as governments and the private sector move to improve aging railway systems amid the current supply chain crisis.

On Thursday (Nov. 4), St. Louis-based mobility technology firm Intramotev announced that early-stage venture capital fund Idealab X is investing in the company’s eco-friendly rail concept, where trains ditch carbon-spewing locomotives for electric and driverless freight trains.

In a statement, Intramotev Co-founder and CEO Tim Luchini said, “Every day, up to 900,000 of the 1,600,000 active railcars in the US don’t move at all, and loaded railcars sit on average for 24.6 hours on each leg of their journey waiting for diesel locomotives. We envision a future in which freight can move itself without waiting for a locomotive, making the system more efficient and environmentally friendly. The current supply chain crisis further demonstrates the need for technologies that can increase the capacities of the existing freight infrastructure.”

That same day, industry news site Freight Waves reported that “Intramotev’s technology aims to create railcars that can be used autonomously over shorter distances. Whether retrofitted or custom-built with the technology, the railcars could be strung together to form a train — with no locomotive at the helm.” And no engineer, either — unless they’re remotely monitoring.

Rail is a prime mover of heavy freight in big quantities, and is ripe for innovation post-pandemic.

The U.S. Federal Railroad Administration (FRA) notes that the freight rail industry generates roughly $80 billion annually, comprised of “seven Class I railroads (railroads with operating revenues of $490 million or more) and 22 regional and 584 local/short line railroads.”

While Intramotev is driven largely by a desire to reduce emissions, the FRA notes that rail achieves what other modes can’t, including “reductions in road congestion, highway fatalities, fuel consumption, greenhouse gases, cost of logistics and public infrastructure maintenance costs.”

See also: Industries Try Allocations, Alternate Vendors and New Forms of Transportation to Work Around Supply Chain Problems

Data, Devices Helping to Drive Autonomous Mobility Forward

Other use cases for autonomous trains center on increasing urban mobility needs for humans.

In October, Deutsche Bahn (DB) and Siemens Mobility unveiled “the world’s first train that operates by itself in rail traffic.”

In a statement, Siemens AG CEO Dr. Roland Busch said, “We are making rail transport more intelligent. Trains drive the perfect timetable automatically, accurate to the second and energy-optimized.” The week before Deutsche Bahn (DB) and Siemens Mobility unveiled its autonomous commuter train, it took its first trip in the German city of Hamburg.

EuroNews reported that “beginning in December, four autonomous trains created by Siemens and Deutsche Bahn will enter service in the northern German port city as part of a €60 million modernization project for its S-Bahn urban rail system.”

AI, IoT devices and masses of data are core to new freight and passenger train concepts. A recent whitepaper on the use of AI and connected data from edge computing firm ADLINK notes that “the amount of data produced in the rail industry continues to grow exponentially. Over time, large amounts of structured and unstructured information, also called ‘big data,’ flows from multitudes of devices and services, such as sensors, smartphones, servers and databases. This volume of data gives the rail industry ample reason to use AI, which can deeply analyze how rail systems may improve efficiency, safety, customer approval and profits.”

Emerging mobility use cases involve not only AI and IoT, but also machine-to-machine (M2M) tech, “a subset of IoT devices that communicate directly with other connected on-premises or cloud services, [and] are also data-collecting devices. Vending machines, trackers, meters and point-of-sale systems all fall under M2M, transmitting changes and information across a wired or wireless point-to-point network to a waiting server,” per the ADLINK white paper.

The Brussels-based International Association of Public Transport recently completed a four-year study in concert with EU-funded research project GECKO (Governance for New Mobility Services), exploring connected mobility solutions for the European Union and elsewhere.

An October 2021 brief prepared by the two entities identifies primary areas of focus on new connected mobility solutions covering the spectrum from mass mobility to autonomous cars.

Per the brief, these include vehicles “that connect to other vehicles and/or devices, networks and services outside the car including the internet, other cars, home, office or infrastructure,” automated vehicles with “technology available to assist the driver so that elements of the driving task can be transferred to a computer system,” innovation in infrastructure “defined as management through pricing, taxation, digitalization and integration,” and “mobility as a Service (MaaS) … the integration of, and access to, different transport services in one single digital mobility offer, with active mobility and an efficient public transport system as its basis.”

See also: Visa Mobility Study: Most Want Contactless Payments on Public Trans