FW-HTF-P: Building Human-Technology Safety Partnerships in Roadside Work Zones

据报道，公路建设和维护是美国最不安全的职业之一。与其他职业相比，道路工人在工作中受伤或死亡的可能性高出六倍。在过去的二十年中，超过22，000名公路建设和维护工人死于与工作有关的事故，这意味着每年的社会成本为5500万美元。然而，实时提醒工人紧急情况是非常困难的，因为工作环境嘈杂而混乱，充满了视觉干扰，强烈的振动和巨大的噪音。确定威胁和采取适当行动是非常具有挑战性的，特别是在可供作出反应的时间非常短暂的情况下。该项目探讨了使用可穿戴技术创建智能工作区的概念，以提高工人的安全舒适度。这种可穿戴设备将帮助工人识别和警告潜在的威胁/危险情况，提供初步的先发制人的指导，并帮助他们找到安全的方法。该研究团队的目标是：1）为培训工人提供基于虚拟现实（VR）的工具; 2）为机构和承包商提供新兴社会技术领域工人安全的最佳实践指南。一个由科学家、公共/私人利益相关者和行业合作伙伴组成的聚合研究团队将（1）开发连接可穿戴设备的初始原型（2）使用虚拟现实实验来调查工人在危险事件中的行为以及有无可穿戴设备的安全相关决策（Future Worker）;以及（3）开发一种新的技术接受模型，并量化这种新的人类-技术安全伙伴关系的社会/经济效益（Future Work）。成功的项目成果将被整理成一个培训和学习平台（SHIELD：实验室和司机的危险识别和规避科学），启动一个长期的研究路线图，这将有助于工作区安全技术的设计选择。SHIELD平台将提供现实而安全的学习环境，在这种环境中，可以测量未来工人在各种危险情景下的规避行为数据，以便为人类-技术安全伙伴关系提供信息。该项目产生的VR培训模块将改善工人对可穿戴设备能力和整体态势感知的心理模型，从而使工人和组织能够制定由新增强的物理能力提供的新安全策略。对不同工人的学习和适应的科学见解将有助于使技术设计更具包容性和有效性，并确保公平的劳动力多样化。最终的目标是使SHIELD平台可扩展并可转移到其他几个具有碰撞危险的工作环境中，无论是车辆（例如，火灾响应者、拖曳、废物清除、路边援助和执法）或通过坠落或飞行物体（例如，该奖项反映了NSF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。

Highway construction and maintenance is reported as one of the most unsafe occupations in the United States. Road workers are six times more likely to be injured or killed during work, compared with other occupations. In the past two decades, more than 22,000 highway construction and maintenance workers have died due to work-related accidents, which translates to a societal cost of $55 million/year. Nevertheless, alerting a worker to an emergency in real-time is extremely difficult, as the work environment is noisy and chaotic, filled with visual distractions, heavy vibrations, and loud noises. Identifying threats and taking appropriate action is very challenging, especially when the time available to respond is very brief. This project explores the concept of using connected wearable technology to create smart work zones that would enhance workers' safety & comfort. This wearable device would assist workers in identifying and warning of potential threats/hazardous situations, give initial preemptive guidance, and help them find a way to safety. The research team aims 1) to provide virtual reality (VR)-based tools for training workers and 2) to provide agencies and contractors with guidelines for best practices for worker safety in the emerging sociotechnical landscape.A convergent research team of scientists, public/private stakeholders, and industry partners will (1) develop an initial prototype of connected wearable devices (Future Technology); (2) use VR experiments to investigate workers' behavior during hazardous events and safety-related decisions with and without wearable devices (Future Worker); and (3) develop a novel technology acceptance model and quantify the societal/economic benefits of this new human-technology safety partnership (Future Work). Successful project outcomes will be collated into a training-and-learning platform (SHIELD: the Science of Hazard Identification and Evasion for Laborers and Drivers), initiating a long-term research roadmap that will facilitate design choices for work zone safety technology. The SHIELD platform will provide realistic yet safe learning environments in which data on future workers' evasive behavior in various struck-by-hazard scenarios can be measured in order to inform the human-technology safety partnership. The VR training modules resulting from this project will improve the workers' mental model of the wearable device capabilities and overall situational awareness, thereby enabling workers and organizations to formulate new safety strategies afforded by the newly augmented physical capabilities. The scientific insights on learning and adaptation across a diverse range of workers will help make the technology designs more inclusive and effective and ensure equitable workforce diversification. The eventual aim is to make the SHIELD Platform scalable and transferable to several other work contexts with struck-by hazards, either by vehicles (e.g., fire respondents, towing, waste removal, roadside assistance, and law enforcement) or by falling or flying objects (e.g., mining, general construction, oil, and gas).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.