FW-HTF-RL: Reimagining Trucking: Forging an Equitable and Driver-Centered System in a Highly Automated World

University Of Massachusetts Amherst, Amherst MA

Investigators

Abstract

Automated commercial motor vehicles (ACMVs), especially long-haul trucking, will transform a large segment of the US economy and the millions of workers that support it. This Future of Work at the Human-Technology Frontier - Research: Large (FW-HTF-RL) award supports research to investigate whether automation can be designed to lead to reskilling and new job opportunities rather than deskilling work and widening inequalities. ACMVs provide improved safety, enhanced fuel economy, and lower travel times, and most importantly, offer a potential solution to growing supply chain and trucker shortage problems. However, ACMVs' relationship to work performed by truckers as we know it is more uncertain. It is undeniable that the current human-technology partnership will change as more automated technology is introduced into the truck. This research project seeks to build new knowledge on the challenges of automation and reimagine this partnership from a human-centered approach to the future of trucking. The investigators will do that by informing the dignity of work and reskilling the development of an interface where truckers will interact in new and productive ways with the automated truck and the trucking functions; with these activities being completed from a worker's perspective. Results from this project could benefit workers in other contexts in which automation and AI-powered systems transform the future of work. The research team will focus on the collaboration between the trucker and ACMV. This project brings together expertise in social sciences, computational sciences, human factors, and transportation engineering to achieve multiple convergent goals: (1) an analysis of the technology while promoting human-truck symbiosis; (2) engaging with workers to gain knowledge of their experiences in different contexts; and (3) investigating the work to develop policies for more effective, forward-looking skills, and training. Organizational contexts, interface designs, and AI technologies that could promote inclusion are examined, as well as how technology can broaden opportunities within the trucking workforce. A range of research methods — from qualitative photovoice, quantitative workforce analysis, and computational decision analysis of AI and human systems to transportation engineering design assessments — are employed in this transdisciplinary project. Overall, this research project launches a much-needed conversation about the future of trucking and contributes to reimagining the future of the entire trucking ecosystem in more human-centered, equitable ways. It yields knowledge for translation into new policies, practices, training programs, and technology. It also engages broad audiences in needed conversations about career paths for truckers by developing a more dynamic and adaptable definition of work and workers that appeals to a more diverse pool of potential truckers. This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to promote a deeper fundamental understanding of the interdependent human-technology partnership in work contexts by advancing the design of intelligent work technologies that operate in harmony with human 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.