Autonomous trucks: drivers remain, for lower-paid tasks

Autonomous trucks: drivers remain, for lower-paid tasks

Image: Most likely automation scenario, absent policy intervention.

University of Pennsylvania sociologist Steve Viscelli has conducted a thorough study into driverless trucks and has just released his final report Driverless? Autonomous Trucks and the Future of the American Trucker.

The study was conducted on behalf of the Centre for Labor Research and Education at the University of California, Berkeley, and Working Partnerships USA, and questioned whether autonomous trucks will mean the end of the road for truck drivers. His findings are summarised below.

Will autonomous trucks mean the end of the road for truck drivers? The USD 740-billion-a-year US trucking industry is widely expected to be an early adopter of self-driving technology, with numerous tech companies and major truck makers racing to build autonomous trucks. This trend has led to dozens of reports and news articles suggesting that automation could effectively eliminate the truck-driving profession.

By forecasting and assessing multiple scenarios for how self-driving trucks could actually be adopted, this report projects that the real story will be more nuanced but no less concerning.

Autonomous trucks could replace as many as 294,000 long-distance drivers in the US, including some of the best jobs in the industry. Many other freight-moving jobs will be created in their place, perhaps even more than will be lost, but these new jobs will be local driving and last-mile delivery jobs that — absent proactive public policy — will likely be misclassified independent contractors and have lower wages and poor working conditions.

Throughout this transformation, public policy will play a fundamental role in determining whether we have a safe, efficient trucking sector with good jobs or whether automation will exacerbate the problems that already pervade some segments of the industry. Trucking is an extremely competitive sector in which workers often end up absorbing the costs of transitions and inefficiencies. Strong policy leadership is needed to ensure that the benefits of innovation in the industry are shared broadly between technology companies, trucking companies, drivers, and communities.

The findings are based on in-depth industry research and extensive interviews with the full range of stakeholders: computer scientists and engineers, Silicon Valley tech companies, venture capitalists, trucking manufacturers, trucking firms, truck drivers, labour advocates and unions, academic experts, and others.

How many will go – 294,000 or 2.1 million?

Prior studies and news stories have suggested that nearly all of the roughly 2.1 million heavy-duty truck drivers in the United States could lose their jobs to automation. However, that number includes many industry segments that are unlikely to be automated in the near future, such as local pickup and delivery and carriers using specialised equipment. This report finds that the jobs most at risk of displacement are long-distance driving jobs with few specialised tasks, representing about 294,000 drivers.

What is likely to happen?

This study is based on an analysis of six potential scenarios for how self-driving technology could be used in the trucking industry. The scenarios are the result of interviews with engineers, developers, trucking firms, and drivers, along with reviews of industry trade literature.

Human–human platooning. A series of human-driven trucks would be electronically linked, with the lead truck controlling speed and braking in the following truck(s). This approach would let the trucks travel much closer together on the highway, improving aerodynamics and fuel efficiency. Each truck would still have a human driver to maintain the lane and navigate local streets.

Human–drone platooning. Similar to the human–human platoon, except that a single human driver would lead a platoon of autonomous drone trucks on the highway. The human driver would be available to operate the lead truck, manage unexpected situations, or make repairs and ensure safety if a truck broke down mid-route. As in the exit-to-exit scenario below, local drivers would bring loads to an autonomous truck port (ATP) near the highway, where they would swap trailers with the drone trucks for the highway platoon.

Highway automation + drone operation. Human operators would remotely control trucks on local streets and in complicated situations, and then trucks would drive autonomously on the highway. This approach would rely on highly trained dock staff to handle tasks currently performed by drivers, such as inspection and coupling.

Autopilot. Similar to autopilot in airplanes, a human would handle loading and local driving, then sleep in the back of the truck while the computer drove on the highway.

Highway exit-to-exit automation. Human drivers would take care of non-driving tasks and navigate complicated local streets, then swap trailers with self-driving trucks at an ATP next to the highway. The autonomous truck would handle the long-distance freeway driving, then hand off the load at an ATP near the destination.

Facility-to-facility automation. In situations where warehouses and shipping facilities are located near major interstates, autonomous trucks may be able to handle industrial roads (where there are few pedestrians and complex intersections) and drive directly from origin to destination.

Absent significant changes in the policy or economic context, this report concludes that highway exit-to-exit automation is the most likely scenario to be widely adopted in the future. However, human-led platoons represent a model that has fewer technological challenges, a strong economic case, and better jobs for long-distance drivers.

 

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