SBIR Phase II: A Non-invasive Screening Tool to Detect Overweight Trucks on Roads in Real Time

SBIR 第二阶段：实时检测道路上超重卡车的非侵入性筛查工具

• 批准号: 2051992
• 负责人: Shervin Taghavi Larigani
• 金额: $ 97.44万
• 依托单位: STL SCIENTIFIC LLC
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051992&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Non; invasive

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This Small Business Innovation Research Phase II project focuses on the detection and deterrence of overweight vehicles on roads. This technology is developing a practical, economical, and reliable real-time screening tool that does not interfere with traffic flow. Overweight commercial vehicles are a significant contributor to the nation's crumbling roads and bridges because the damage to a road surface increases substantially with the relative load, e.g., the road damage caused by an 80,000-pound truck is thousands of times that of a car which is twenty times lighter than the truck. Any efforts to renovate or build new infrastructures will be hindered without addressing this issue broadly. Nearly 71% of U.S freight ― representing $700.3 billion in economic activity in 2017 ― moves via trucks. Also, overweight trucks are a significant safety risk. Being overweight reduces the maneuverability of the massive vehicle and causes the truck's mechanical components to be prone to failure, which in turn often causes crashes, with significant human and economic tolls, especially if the load is hazardous. The intellectual merit of this project is to effectively and reliably measure the weight of a vehicle and consistently detect overweight trucks without interfering with the traffic flow or the integrity of the pavement. The proposed fully-automated system is a disruptive technology that is non-intrusive and infers the weight of vehicles from a distance using a novel, ultra-high-spatial-resolution, electro-optical system. The product is a user-friendly mobile application that displays to subscribers (government agencies or firms in the private sector) the weight of the relevant vehicle in real time. The proposed system is an internet-of-things system, a combination of proprietary electro-optical system, algorithms, signal processing, artificial intelligence and deep learning, system design and integration.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.

该奖项全部或部分由2021年美国救援计划法案（公法117-2）资助。该小型企业创新研究第二阶段项目的重点是检测和威慑道路上的超重车辆。 这项技术正在开发一种实用、经济、可靠的实时筛选工具，不会干扰交通流量。超重的商用车辆是造成国家道路和桥梁破损的重要因素，因为对路面的损坏随着相对载荷而显著增加，例如，一辆8万磅重的卡车造成的道路破坏是一辆比卡车轻20倍的小汽车的数千倍。 如果不广泛解决这个问题，任何翻新或建设新基础设施的努力都将受到阻碍。 近71%的美国货运-代表2017年7003亿美元的经济活动-通过卡车运输。 此外，超重的卡车是一个重大的安全风险。超重会降低大型车辆的机动性，并导致卡车的机械部件容易发生故障，这反过来又会导致撞车事故，造成重大的人力和经济损失，特别是如果负载是危险的。该项目的智力价值是有效可靠地测量车辆重量，并在不干扰交通流量或路面完整性的情况下持续检测超重卡车。拟议中的全自动系统是一种非侵入式的颠覆性技术，使用一种新颖的超高空间分辨率光电系统从远处推断车辆的重量。该产品是一个用户友好的移动的应用程序，可以向用户（政府机构或私营部门的公司）显示相关车辆的真实的重量。该系统是一个物联网系统，结合了专有的光电系统、算法、信号处理、人工智能和深度学习、系统设计和集成。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。