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Fusion of Airborne and Terrestrial Sensed Data for Real Time Monitoring of Traffic Networks

项目名称：	Fusion of Airborne and Terrestrial Sensed Data for Real Time Monitoring of Traffic Networks
摘要：	This research project will build upon the project team�s current work on real-time object recognition and event extraction from LiDAR scans using unmanned aircraft systems (UAS) on-board processing, while also incorporating a suite of complementary sensors and recent advances in transfer learning and geometry matching techniques. Advanced algorithms will be employed to fuse the objects recognized from multiple sources, increasing the accuracy and robustness of traffic network monitoring and detection of features/events of interest. A key benefit of the terrestrial sensors will be to enable the construction of recognition maps, even when UAS data acquisition is infeasible due to regulatory and/or logistical considerations. The proposed solution relies on the collection of recognized objects from the same site by different sensing sources, which are then transmitted to a fusion center. This fusion center will apply transfer learning and geometry matching techniques to both create correspondences between these detected objects (i.e., determine which object corresponds to which other object across the different data sets) and add undetected objects/zones by some of the sources into their proper positions. The final integrated recognition map will provide much richer and more robust information to traffic network controllers, thus enabling data-driven optimization and efficiency for transportation networks.
状态：	Active
资金：	80000
资助组织：	Office of the Assistant Secretary for Research and Technology
管理组织：	University of Idaho, Moscow
项目负责人：	Sorour, Sameh
执行机构：	University of Idaho, Moscow
主要研究人员：	Sorour, Sameh
开始时间：	20180816
预计完成日期：	20200815
实际结束时间：	0