One of the challenges of adoption for any new technology–and especially enterprise or industrial technology–is getting the ball rolling. So while people have been making fantastic claims about things like IoT and driverless vehicles, that may in the end turn out to be true, my question is: where is the first clear ROI case going to be made that stimulates adoption? What spreadsheet-focused, ROI-driven business manager is going to look at the technology and say, “Okay, I can see why we should spend this much now to save or secure this much in the future?”

For the first part of that argument, the main inefficiency in trucking is that humans are operating these commercial vehicles. A driver in the U.S. can’t drive more than 11 hours in a 24-hour period without taking a 10-hour break, and is limited to 14 hours of work (including work at loading docks or doing administrative work) a day. Moreover, drivers are limited to a 60/70 hour limit over 7/8 consecutive days, after which they require 34 hours to restart a new period. In other words, in a 7-day work week comprising 168 hours, more than 75% of potential driving time is lost to human regulations.

And the human assets–the drivers–are hard to come by. The American Trucking Association reported in 2014 that the shortage of truck drivers–especially long-haul, who are often required to spend weeks away from home–was 38,000 drivers. More inefficiency! The machines or vehicles themselves can be widely available and could theoretically go 24/7.

Now, let’s turn to the technical challenges. Purely driverless vehicles on busy urban or suburban streets pose a significant challenge, but one that’s being gradually met and will become much easier once ultra-low-latency, ultra-high-reliability IoT technologies hit the road with 5G adoption. But trucking? A significant percentage of trucking—especially long-haul—involves loading up at a dock or storage facility that’s within a half-mile of a major highway on-ramp, accessed by straightforward industrial park streets designed for trucks, and offloading at a similar facility a very long distance away, with only open highway in between.

As far as technical challenges go, this is not very demanding. Furthermore, this also points out the key value areas where human assets could be re-purposed. Also, this new business paradigm opens up job opportunities in automation and optimisation. These jobs are local and not limited by the above restrictions. And in the short-term, driverless trucks will likely need to go through a driver-assist phase to validate their viability, both from an economic and safety standpoint. One fatality based on a driverless truck, and that compelling ROI delivery will quickly disappear.

To illustrate the progress to date—last month, a convoy of nearly a dozen trucks drove mostly-autonomously across Europe in a week-long challenge. The trucks started in Sweden, Denmark, Belgium, and Germany and ended their journey in port of Rotterdam in the Netherlands using the platooning technique and linked by Wi-Fi. This demonstration is just one example that self-driving trucking could be just around the corner. Within in the U.S., companies such as Daimler and Volvo trucks have debuted self-driving systems in recent months as well. And a new company, Otto, has formed with the goal of turning legacy commercial trucks into self-driving trucks by retrofitting hardware kits to existing truck models. The company is focused primarily on highway driving and has begun to test with the Volvo VNL 780. However, there is not yet a timeline for the release of a commercial product.

In conclusion, these systems require all-new fleets of trucks which may inevitably delay adoption. Big-rigs last a decade and nearly a million miles, and trucks can cost $100-300K (₹ 67.57 lakh – ₹ 2.03 crore) to get the latest technology. However, given the simplicity and compelling nature of the ROI delivery, and recent technical advances and trials, I expect that it will be driverless trucks that will kick off the wave of driverless vehicles.