Computer vision-based condition assessment of the public transit infrastructure assets

基于计算机视觉的公共交通基础设施资产状况评估

• 批准号: 561003-2020
• 负责人: RezazadehAzar, Ehsan
• 金额: $ 2.19万
• 依托单位: Lakehead University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=707168
• 关键词: Computer; vision; based; condition; assessment

Public transit systems are essential to the social and economical prosperity of Canada, and contribute to the advancement of social equity and environmental objectives. Efficient and effective infrastructure asset management is vital to providing a reliable public transit system, but current infrastructure asset management practices mainly rely on conventional data gathering methods which require manual site visits that are labour-intensive and time-consuming. Effective asset management could be more challenging for small and medium-sized cities due to unsteady and limited public revenues. Since transit agencies have difficulties in maintaining and updating their large datasets using their limited human resources, many research efforts have focused on development of semi-automated infrastructure condition assessment methods, such as crowdsourcing by the online community, image and video processing, aerial photography, and vehicle-based LiDAR. The proposed research project will develop an innovative computer vision-based system to improve data collection and condition assessment processes for public transit infrastructure asset management. The proposed system will use the regular operation of the transit buses for data collection and then utilizes deep learning methods to detect public transit infrastructure assets, asses their condition, and update asset management inventories. The industry partners in this research project are Thunder Bay Transit and Consat Telematics. Thunder Bay Transit provides general public transit services in Thunder Bay area and aims to incorporate the findings of this research to enhance management of their infrastructure assets. Consat Telematics is a technology company which develops intelligent transportation systems and the developed system will be integrated into their fleet management systems.

公共交通系统对于加拿大的社会和经济繁荣至关重要，并有助于促进社会公平和环境目标。高效且有效的基础设施资产管理对于提供可靠的公共交通系统至关重要，但当前的基础设施资产管理实践主要依赖于传统的数据收集方法，需要人工现场访问，既费力又耗时。由于公共收入不稳定且有限，有效的资产管理对于中小城市来说可能更具挑战性。由于交通机构难以利用有限的人力资源来维护和更新大型数据集，因此许多研究工作都集中在半自动化基础设施状况评估方法的开发上，例如在线社区众包、图像和视频处理、航空摄影和车载激光雷达。拟议的研究项目将开发一种基于计算机视觉的创新系统，以改进公共交通基础设施资产管理的数据收集和状况评估流程。拟议的系统将利用公交巴士的常规运营来收集数据，然后利用深度学习方法来检测公共交通基础设施资产，评估其状况并更新资产管理库存。该研究项目的行业合作伙伴是 Thunder Bay Transit 和 Consat Telematics。 Thunder Bay Transit 在 Thunder Bay 地区提供一般公共交通服务，旨在将这项研究的结果纳入其中，以加强其基础设施资产的管理。 Consat Telematics是一家开发智能交通系统的科技公司，开发的系统将集成到其车队管理系统中。