PFI-RP: Commercialization of Automotive Lane Line Detection Software for Snow-Covered Roads

PFI-RP：积雪道路汽车车道线检测软件的商业化

• 批准号: 2213946
• 负责人: Zachary Asher
• 金额: $ 55万
• 依托单位: Western Michigan University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2213946&HistoricalAwards=false
• 关键词: PFI; RP; Commercialization; Automotive; Lane

The broader impact/commercial potential of this Partnerships for Innovation – Research Partnerships (PFI-RP) project is improved transportation safety and usability for the general public during adverse weather conditions. Additionally, this project seeks to develop and commercialize new computer vision and machine learning techniques that can be applied to other applications, facilitating engagement from the automotive industry in addressing inclement weather driving problems and enabling entrepreneurial engagement from underrepresented communities. Achievement of safe vehicle operation in adverse weather has further implications associated with the widespread deployment of automated vehicles and features including improved efficiency to combat climate change, improvements in ground vehicles for military applications, and a stronger transportation network design and management. Students from underrepresented communities will be recruited and receive training in translational research and entrepreneurship through engagement with existing university-wide organizations. The proposed project seeks to develop automated vehicle computer vision for adverse weather which, despite being commonly identified as a needed product, has received relatively little attention in the marketplace. The proposed technology utilizes automotive cameras, computer vision, systems engineering principles, and refined methods of machine learning without an overreliance on deep learning. The translation and commercialization of computer vision algorithms into a fully automated vehicle systems with embedded hardware requires a multidisciplinary approach requiring academic, industrial, and entrepreneurial competence. The four key technical barriers include data scale-up, module improvements, vehicle integration, and use of embedded hardware. Because the identified minimum viable product is designed for safe automated driving in snow, the team is pursuing winter season milestones that include large dataset collection, module improvements with an associated vehicle integration demonstration, and a complete minimum viable product demonstration with potential business partners and customers. The project goal is successful commercialization of an automotive lane line detection software for snow-covered roads.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.

该创新-研究伙伴关系（PFI-RP）项目的更广泛影响/商业潜力是在恶劣天气条件下改善公众的运输安全性和可用性。此外，该项目旨在开发和商业化可应用于其他应用的新计算机视觉和机器学习技术，促进汽车行业参与解决恶劣天气驾驶问题，并使代表性不足的社区能够参与创业。在恶劣天气下实现安全的车辆操作具有与自动化车辆和特征的广泛部署相关的进一步影响，包括提高应对气候变化的效率，改进用于军事应用的地面车辆，以及更强大的运输网络设计和管理。来自代表性不足的社区的学生将被招募，并通过与现有的大学范围内的组织接触，接受翻译研究和创业培训。拟议的项目旨在开发针对恶劣天气的自动车辆计算机视觉，尽管通常被认为是一种必要的产品，但在市场上受到的关注相对较少。该技术利用了汽车摄像头、计算机视觉、系统工程原理和完善的机器学习方法，而不会过度依赖深度学习。将计算机视觉算法转化和商业化到具有嵌入式硬件的全自动车辆系统中需要多学科方法，需要学术，工业和创业能力。四个关键技术障碍包括数据扩展、模块改进、车辆集成和嵌入式硬件的使用。由于确定的最低可行产品是为雪地安全自动驾驶而设计的，因此该团队正在追求冬季里程碑，包括大型数据集收集，相关车辆集成演示的模块改进，以及与潜在业务合作伙伴和客户的完整最低可行产品演示。该项目的目标是成功商业化的汽车车道线检测软件的积雪覆盖的道路。这个奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的知识价值和更广泛的影响审查标准的支持。

项目成果

Road Snow Coverage Estimation Using Camera and Weather Infrastructure Sensor Inputs

使用相机和天气基础设施传感器输入估算道路积雪覆盖范围

• 发表时间: 2023
• 期刊: SAE World Congress
• 作者: Kadav, Parth;Goberville, Nicholas A;Prins, Kyle;Siems-Anderson, Amanda;Walker, Curtis;Motallebiaraghi, Farhang;Carow, Kyle;Rojas, Johan Fanas;Hong, Guan Yue;Asher, Zachary D.
• 通讯作者: Asher, Zachary D.

Projecting Lane Lines from High-Definition Maps for Automated Vehicle Perception in Road Occlusion Scenarios

从高清地图投影车道线，以实现道路遮挡场景中的自动车辆感知

• 发表时间: 2023
• 期刊: SAE World Congress
• 作者: Carow, Kyle;Kadav, Parth;Rojas, Johan Fanas;Asher, Zachary D.
• 通讯作者: Asher, Zachary D.