Benefit Cost Analysis of Railroad Track Monitoring Using Sensors On-Board Revenue Service Trains
项目名称: Benefit Cost Analysis of Railroad Track Monitoring Using Sensors On-Board Revenue Service Trains
摘要: This study will develop, implement, and evaluate a benefit cost analysis (BCA) method to assess the benefits and costs of implementing an autonomous track geometry monitoring system to screen the network for faults during normal train operations. The BCA will quantify and monetize all potential costs and benefits of the technology deployment. Cost estimates will include research to obtain volume dependent pricing for equipment from key manufacturers of all the required system components. A complete autonomous track geometry monitoring system will include wireless sensors, energy harvesting devices, wireless access points, cloud computing resources, and maintenance. Costs such as a first installation may be one-time and other costs such as wide-area network communications and a cloud-service subscription may be recurring. Hence, some of the cost changes may be non-linear over time because of technology commoditization and the dynamic costs for cloud computing services. Quantifying the benefits will involve research and analysis to estimate time and monetary savings for track inspections and the reduction of track closures. Other potential benefits are from derailment risk reduction due to more regular inspections. The study will also describe any benefits that are not quantifiable in monetary terms, such as the use of standard web interface tools, the convenience of data visualization, and the modernization of asset management systems that incorporate the technology. In addition, this study will conduct an uncertainty and sensitivity analysis of the BCA under various scenarios proposed by Federal Railroad Administration (FRA) stakeholders.
状态: Active
资金: 129022
资助组织: Office of the Assistant Secretary for Research and Technology
管理组织: Mountain-Plains Consortium
项目负责人: Kline, Robin
执行机构: Upper Great Plains Transportation Institute
主要研究人员: Lu, Pan
开始时间: 20171201
预计完成日期: 20220731
实际结束时间: 0
检索历史
应用推荐