Collaborative Research: FW-HTF-R: The Future of Trucking: Pathways to Positive Societal Outcomes

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

The long-distance trucking industry is poised to be an early adopter of vehicle automation. Significant technological challenges need to be resolved before long-distance trucking can work safely without substantial human oversight. This research team effort is motivated by a shared belief that remote operation of trucks is a necessary step in the automation journey and will lead to positive technological, economic, environmental, and societal outcomes. As-needed remote operation could fundamentally transform trucking into something closer to a white-collar job, requiring human-computer interaction, in a controlled and scheduled environment. It would eschew long hours by drivers on the road, far from home, and likely change the skills and characteristics of the job in ways that will have gender/racial equity, health, and socio-economic implications. What technological problems must be solved for a truck to safely operate almost entirely autonomously, with a remote operator intervening on request or as warranted when the autonomy stack is challenged? How will the nature of the trucking occupation change, and what does it portend for current and future workers? We propose an integrated effort that innovates on remote operation technology and identifies concomitant changes in policies, regulations, and skills (including (re)training requirements) to positively affect the number and quality of jobs and improve outcomes for all stakeholders. This research will be informed by key stakeholders: drivers, independent owner-operators, shipping firms, regulators, vehicle manufacturers, and automation developers. In the Future technology context, this project will: (i) develop a data-driven and simulation-informed system that can continuously monitor and predict challenging traffic conditions, (ii) develop a robust safety filter that mediates the commands issued by the local autonomy stack and the remote human operator, (iii) establish a cooperative architecture and algorithms for automated trucking, and (iv) identify network solutions to meet the communication needs of remote operation. In the Future work component, this project will: (i) investigate information requirements of remote operators and techniques to balance automated in-vehicle control with remote control by an operator, (ii) explore managing operators’ attention and level of control across multiple trucks, and (iii) address critical regulatory issues and how to balance operator compensation, firm profitability, and technology adoption. In the Future worker category, this project will: (i) evaluate expected changes in the distribution of occupations and skill requirements in the workforce, (ii) assess the impact of job creation and loss on rural economies, and (iii) elucidate the skill and demand changes for truckers and the new training needed for these workers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.