详情

Smart and Cooperative Truck Parking Monitoring and Calibration System Empowered by Machine Learning

项目名称：	Smart and Cooperative Truck Parking Monitoring and Calibration System Empowered by Machine Learning
摘要：	The primary goal of this research is to create a truck parking monitoring and calibration system empowered by machine learning, for the in/out truck parking counting system. Four components will be integrated into the proposed system, including (1) the truck parking lot sensing component, (2) the information collection component, (3) the sensing anomaly detection component, and (4) the cooperative monitoring and calibration component. Counting data can be obtained by the installed sensors, i.e., radars, cameras, and etc., at the entrance and exit at a truck parking lot. A separate video surveillance system will also be installed to collect ground-truth data. Then, the real-time parking occupancy can be calculated, and the anomaly status can be identified based on the comparison with ground-truth records. The next step is to send the collected information, such as real-time or historical ground-truth occupancy sequence and the anomaly detection results, into the cooperative calibration component. Finally, the proposed system can generate the calibrated occupancy result, confidence rate, sensing system status and calibration recommendations. To achieve this goal, the research team has identified four objectives: (1) propose a real-time truck parking sensing system status anomaly detection framework; (2) propose a real-time parking lot occupancy estimation empowered by deep learning; (3) propose a human-machine cooperative monitoring and calibration algorithm empowered by sequence classification; and (4) build a live website to visualize the truck parking sensing monitoring and calibration result.
状态：	Active
资金：	100000
资助组织：	Washington State Department of Transportation
项目负责人：	Brodin, Doug
执行机构：	University of Washington, Seattle
主要研究人员：	Wang, Yinhai
开始时间：	20220916
预计完成日期：	20231231
主题领域：	Freight Transportation；Motor Carriers；Operations and Traffic Management