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

FW-HTF-RL：重新构想卡车运输：在高度自动化的世界中打造公平且以驾驶员为中心的系统

• 批准号: 2326054
• 负责人: Shannon Roberts
• 金额: $ 200万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2326054&HistoricalAwards=false
• 关键词: FW; HTF; RL; Reimagining; Trucking

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.

自动化商用机动车辆（acmv），尤其是长途卡车运输，将改变美国经济的很大一部分以及为其提供支持的数百万工人。这项人类技术前沿工作的未来-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培训和新的工作机会，而不是使工作失去技能和扩大不平等。acmv提高了安全性，提高了燃油经济性，缩短了行驶时间，最重要的是，它为日益增长的供应链和卡车司机短缺问题提供了潜在的解决方案。然而，据我们所知，acmv与卡车司机的工作之间的关系是不确定的。不可否认的是，随着更多的自动化技术被引入卡车，目前的人类技术伙伴关系将发生变化。该研究项目旨在建立有关自动化挑战的新知识，并从以人为本的方法重新构想这种伙伴关系，以实现卡车运输的未来。调查人员将通过宣传工作的尊严和重新培训界面的开发来实现这一目标，在这个界面中，卡车司机将以新的、富有成效的方式与自动卡车和卡车运输功能互动；从工人的角度来完成这些活动。这个项目的结果可以使自动化和人工智能系统改变未来工作的其他环境中的工人受益。研究小组将重点研究卡车司机和ACMV之间的合作。该项目汇集了社会科学、计算科学、人为因素和交通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，了解他们在不同背景下的经验；(3)调查制定更有效、更具前瞻性的技能和培训政策的工作。研究了可以促进包容性的组织环境、界面设计和人工智能技术，以及技术如何在卡车运输劳动力中扩大机会。这个跨学科项目采用了一系列研究方法——从定性光声、定量劳动力分析、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。总的来说，这项研究项目启动了一场关于卡车运输未来的急需对话，并有助于以更以人为本、更公平的方式重新构想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。它还通过制定一个更具活力和适应性的工作和工人定义，吸引更多样化的潜在卡车司机群体，让广泛的受众参与到有关卡车司机职业道路的必要对话中。该项目由人类-技术前沿跨部门计划的未来工作资助，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类-技术伙伴关系的更深层次的基本理解。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。