How Automation Technology is Transforming the Freight Industry

The economic and technological pressures of foreign policy and an on-demand society are changing the competitive landscape of the freight transit industry. Freight demand is growing at an unprecedented rate at a time when operators are already in a capacity crunch. Financial constraints aside, there is simply not enough physical space to support adding more infrastructure. Even if there were, more road and rail couldn’t be built fast enough to meet demands. In the past, such challenges could be solved with more concrete and iron. Today, however, we must address these issues with digital solutions driven by operationalizing the immense amount of data generated by freight operations. The future of all societies will be directly impacted by how we alleviate increasing demands on the freight industry.

Improving Throughput

There are two factors that could be key to solving this issue—throughput and availability of freight transport. Simply adding more freight assets such as trains and trucks will not increase the throughput of our existing infrastructure; in fact, adding more mobile assets would simply clog up an already overcrowded system, not to mention that the required human resources to operate them don’t exist. To increase throughput, freight industries will need to turn to automation. Automation does more than remove logistical constraints and service hour regulations, such as the 12-hour limit for rail crews. It also allows for new operational rules that are no longer governed by human factors. Automation enables speed limits to be localized for a section of road or track down to the mile per hour, freeing vehicles once subjected to 5 mile-per-hour designations and rules governing how often they can change speed. The ability to operate vehicles much closer together, with strategies such as “platooning” for trucks or “moving block” for trains, can become standard operation. These enhanced operating modes are what will increase the throughput of the network and are empowered by automation technology.

New Challenges for Asset Availability

Asset availability is the second pillar in addressing the challenges of freight transport demand. Drivers today drive by the “seat of their pants,” feeling the response of the vehicle in their seat. They are attuned to the harmonic song of the vibrations and sounds of the vehicle and can often detect anomalies and defects before they occur. As automation evolves and drivers are moved to specialized missions and asset recovery, this sixth sense fades away, and those defects that were once caught by an experienced human will be left to a machine to identify. In addition, what were previously simple fixes addressed by drivers will have a greater impact, as a reconnaissance team will need to be dispatched to recover a driverless asset. To offset this risk, operationalization of the immense data being generated by the autonomous system must be utilized to generate predictive maintenance insights. Addressing potential failures while an asset is in the shop becomes critical to realizing the value of automation and delivering on the promised increase in throughput. Predictive Maintenance is already working its way into more and more maintenance strategies and gaining acceptance. Even more so, the sensor packages that come with outfitting an asset for automation provide more data than we have ever had to work with before and will only lead to increased performance of these insights.

Like autopilot for an aircraft, automated freight assets will still need the driver (like the pilot in planes) to oversee operations, make sure the system works as intended and recover driverless assets that have experienced an equipment failure. There will be no more powerful solution than a machine-informed human expert. Automation and human drivers go hand in hand. Automation creates new operational strategies to increase the throughput of our infrastructure, increase the reliability of our assets, and results in a more efficient and safer business.

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