Big Data Driven Vessel Trajectory and NavigatingState Prediction

主题：Big Data Driven Vessel Trajectory and NavigatingState Prediction
主要内容：The predictive vessel surveillance is one of the indispensable functional components in intelligent maritime traffic system. Vessel trajectory prediction serves as a prerequisite for collision detection and risk assessment. The availability of maritime big data brings great potential to extract vessel movement patterns to support trajectory forecasting. A novel vessel trajectory and navigating state prediction methodology is proposed based on AIS data, which synergizes properly designed learning, motion modelling and knowledge base assisted particle filtering processes. The primary contributions of this work also comprise several critical research findings to handle the key challenges in vessel trajectory and navigating state prediction problem, such as the adaptive training window determination for the learning process and effective knowledge storage and searching algorithm intended to reduce the query time of waterway pattern retrieval. With the maritime traffic data collected for Singapore water, a thorough evaluation of the prediction performance has been conducted for different navigating scenarios.
专家姓名：张立业
工作单位：山东科技大学
专长和学术成就：主要从事智慧交通方面的研究，研究方向包括交通大数据理论与方法、高性能交通仿真与优化、智慧港口、车联网交通等。 截至目前，在国内外交通运输工程研究领域发表学术论文40余篇，其中《Transportation Research Part A, E》《IEEE transactions on intelligent transportation systems》等SCI/SSCI期刊收录论文20余篇，主持新加坡-德国联合攻关项目、新加坡自然基金重点项目、新加坡港口局创新研发等项目等10余项，参与中国国家自然科学基金、国家重点研发计划项目等多项，研究成果被亚洲新闻等媒体报道，多项成果被用于新加坡的城市交通管理和港口海运交通管理。任世界交通运输大会（WTC）技术委员会委员，为Transportation Research Parts A、B,C, D,E等10余个SCI国际期刊的同行评审专家。
专家简介：张立业，男，出生于1981/11，山东科技大学交通学院教授/博士生导师，泰山学者，博士毕业于同济大学交通规划与管理专业，国家公派美国佛罗里大学联合培养博士生，前新加坡科学院高性能计算研究所（Institute of High Performance Computing, IHPC）科学家，曾任新加坡国立大学海事研究中心研究员。
时间：2021-11-08 13:30:00
地点：交运209