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

自动化商用汽车(ACMV)，特别是长途卡车运输，将在很大程度上改变美国经济的一大部分，并改变数百万支持它的工人。人类技术前沿的未来工作-研究：大型(FW-HTF-RL)奖支持研究，以调查自动化是否可以被设计为导致重新技能和新的就业机会，而不是去技能工作和日益扩大的不平等。ACMV提供了更好的安全性、更好的燃油经济性和更短的出行时间，最重要的是，它为日益严重的供应链和卡车短缺问题提供了潜在的解决方案。然而，ACMV与我们所知的卡车司机所从事的工作的关系更不确定。不可否认，随着更多自动化技术被引入卡车，目前的人-技术伙伴关系将发生变化。这项研究项目寻求建立关于自动化挑战的新知识，并重新设想这种伙伴关系从以人为中心的方法到卡车运输的未来。调查人员将通过告知工作的尊严和重新掌握接口的开发来做到这一点，在该接口中，卡车司机将以新的和富有成效的方式与自动卡车和卡车运输功能互动；这些活动将从工人的角度完成。这个项目的结果可能会让自动化和人工智能系统改变工作未来的其他环境中的工人受益。研究团队将专注于卡车司机和ACMV之间的合作。该项目汇集了社会科学、计算科学、人为因素和运输工程方面的专业知识，以实现多个融合目标：(1)在促进人-车共生的同时分析技术；(2)与工人接触，了解他们在不同环境中的经验；以及(3)调查工作，以制定更有效、更具前瞻性的技能和培训的政策。本课程探讨了可促进包容性的组织背景、界面设计和人工智能技术，以及技术如何扩大卡车运输劳动力的机会。在这个跨学科的项目中使用了一系列的研究方法-从定性的PhotoVoice、定量的劳动力分析、人工智能和人类系统的计算决策分析到交通工程设计评估。总体而言，这项研究项目启动了一场关于卡车运输未来的亟需的对话，并有助于以更以人为中心的、公平的方式重新想象整个卡车运输生态系统的未来。它产生的知识可以转化为新的政策、实践、培训计划和技术。它还通过制定更具活力和适应性的工作和工人定义来吸引更多样化的潜在卡车司机，从而让广泛的受众参与到关于卡车司机职业道路的必要对话中。该项目由人类-技术前沿未来工作计划资助，旨在通过推进与人类工人和谐运作的智能工作技术的设计，促进对工作环境中相互依赖的人-技术伙伴关系的更深层次的基本理解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.