学术报告题目：Big Data Applications for Traffic Management Systems
Vehicle positioning and speed data generated by individual vehicles have always been considered as big data for its size and complexity. It has been utilized to generate traffic information. We want to take one step further to incorporate individual vehicle data into traffic control, gradually replacing the role of the existing traffic surveillance systems as the dominant source of traffic data. To prepare for such a paradigm shift, one needs to overcome some key institutional barriers, in particular, the privacy issue. A Highway Voting System (HVS) is proposed to address this issue in which drivers provide link- and/or path-based vehicle data to the traffic management system in the form of "votes" in order to receive favorable service from traffic control. The proposed HVS offers a platform that links data from individual vehicles directly with traffic control. In the system, traffic control responds to voting vehicles in a way similar to the current system responding to priority vehicles and providing the requested services accordingly. Strategies to entice drivers into "voting" so as to increase the market penetration level under all traffic conditions are discussed. Examples are given to demonstrate the impact of the proposed system on algorithm development and traffic control.
海天学者简介：林伟华是美国亚利桑那大学系统与工业工程系副教授，曾任该系教师聘用委员会主席，并于2012年至今一直担任该系教师聘用委员会委员。他分 别在1985年、1989年、1995年于美国三所不同的名校获得了计算机科学专业学士学位、数学专业硕士学位、和土木工程专业博士学位，并在加州大学进 行了为期两年的博士后研究工作，之后任教至今。他在智能交通系统与运输领域中的所有顶级期刊都有第一作者的论文发表，如 Transportation Science、Transportation Research Parts A, B, C, and E、以及 IEEE Transaction on Intelligent Transportation Systems；他目前共发表论文84篇，总引用达 1352次，h因子为17（Google Scholar）。