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

长途卡车运输行业有望成为车辆自动化的先行者。在长途卡车运输能够在没有大量人为监督的情况下安全运行之前，需要解决重大的技术挑战。这一研究团队的努力是基于一个共同的信念，即远程操作卡车是自动化之旅中的必要步骤，将带来积极的技术、经济、环境和社会成果。按需远程操作可以从根本上将卡车运输转变为一种更接近白领工作的工作，需要在受控和预定的环境中进行人机交互。它将避免司机在远离家乡的道路上长时间工作，并可能以具有性别/种族平等、健康和社会经济影响的方式改变工作的技能和特点。必须解决哪些技术问题，卡车才能安全地几乎完全自主地运行，当自动堆栈受到挑战时，远程操作员会根据要求或正当理由进行干预？卡车运输职业的性质将如何改变，它对现在和未来的工人意味着什么？我们建议在远程操作技术方面进行创新，并确定相应的政策、法规和技能(包括(重新)培训要求)的变化，以积极影响工作岗位的数量和质量，并改善所有利益相关者的成果。这项研究将由主要利益相关者提供信息：司机、独立车主运营商、航运公司、监管机构、车辆制造商和自动化开发商。在未来的技术背景下，这个项目将：(I)开发一个数据驱动和模拟信息的系统，可以持续监测和预测具有挑战性的交通状况；(Ii)开发一个强大的安全过滤器，协调本地自主堆栈和远程人类操作员发出的命令；(Iii)建立一个用于自动化卡车运输的合作架构和算法；以及(Iv)确定满足远程操作通信需求的网络解决方案。在未来的工作部分，该项目将：(I)调查远程操作员的信息需求和技术，以平衡自动化车载控制和操作员的远程控制，(Ii)探索管理操作员的注意力和跨多辆卡车的控制水平，以及(Iii)解决关键的监管问题以及如何平衡操作员薪酬、公司盈利能力和技术采用。在未来工人类别中，该项目将：(I)评估职业分布和劳动力中技能要求的预期变化，(Ii)评估创造就业机会和失去工作对农村经济的影响，以及(Iii)阐明卡车司机的技能和需求变化以及这些工人所需的新培训。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。

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.