Parallel Systems, a company established by three former SpaceX engineers has raised USD 53.15 million as of today, of which a $3.6 million seed round, to build autonomous battery-electric rail vehicles and create a more efficient, decarbonized freight network by using the existing railway national infrastructures. Parallel System’s second-generation vehicle aims to launch an advanced test-program to help the startup into the integration of its autonomous vehicles into real operations.
Parallel Systems’ rail-vehicle architecture is addressed to solve the existing rail-ways problems with carbon emissions in freight, supply chain constraints of trucking and limits of railway freight. “Rail has a lot of opportunity to grow when it comes to intermodal, and we focus on this because this is where we think there’s competition and appetite for innovation,” according to co-founder and CEO Matt Soule.
The start-up’s vehicle architecture consists of individually powered rail-cars which can load and transport standard shipping containers as a single or double-stacked load. Those rail-cars can join up to form “platoons” or split-off to multiple destinations while en-route. They can carry much more weight than road-trucks, which are responsible for the handling of most of the freight transportation.
“For the unit economics of freight trains to get competitive with trucks, you need really long trains, and you’re amortizing the cost of that locomotive and crew over that one really long train,” said Parallel’s CEO Soule. “When that becomes a problem is when you’re figuring out where to park that big train, and the answer is, not many places.” ““We can move in smaller platoons and rather than dwelling all day for the unloading and loading operation, we’re in and out within an hour or two, leaving room for other platoons to come in. It’s more efficient footprint and it enables things like serving ports and creating inland port shuttle systems so you can move the containers from a seaport to an inland port, which is often a better place for trucks to go and are closer to warehousing activities.”
Parallel Systems consider railroad’s closed networks as the ideal operational design domain for safe and early commercialization of autonomous technology due to limited track access and centralized traffic control. The company’s developed software is expected to allow the rail-car platoons to safely integrate with existing rail operations, with freight trains and transit inter-operations. The software uses machine learning to provide freight tracking and to optimize vehicle routing, traffic scheduling, as well as energy consumption.