主題：Big Data Driven Vessel Trajectory and NavigatingState Prediction
主要內容：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.
專家姓名：張立業
工作單位：山東科技大學
專長和學術成就：主要從事智慧交通方面的研究，研究方向包括交通大數據理論與方法、高性能交通仿真與優化、智慧港口、車聯網交通等。 截至目前，在國內外交通運輸工程研究領域發表學術論文40余篇，其中《Transportation Research Part A, E》《IEEE transactions on intelligent transportation systems》等SCI/SSCI期刊收錄論文20余篇，主持新加坡-德國聯合攻關項目、新加坡自然基金重點項目、新加坡港口局創新研發等項目等10余項，參與中國國家自然科學基金、國家重點研發計劃項目等多項，研究成果被亞洲新聞等媒體報道，多項成果被用于新加坡的城市交通管理和港口海運交通管理。任世界交通運輸大會（WTC）技術委員會委員，為Transportation Research Parts A、B,C, D,E等10余個SCI國際期刊的同行評審專家。
專家簡介：張立業，男，出生于1981/11，山東科技大學交通學院教授/博士生導師，泰山學者，博士畢業于同濟大學交通規劃與管理專業，國家公派美國佛羅里大學聯合培養博士生，前新加坡科學院高性能計算研究所（Institute of High Performance Computing, IHPC）科學家，曾任新加坡國立大學海事研究中心研究員。
時間：2021-11-08 13:30:00
地點：交運209