报告题目：Big Data Driven Mobility to Tackle Urban Traffic and Electric Vehicle Management

主讲人：许岩岩（Department of Civil and Environmental Engineering, MIT）

报告时间：2017年10月20日（星期五）3:30pm – 4:30pm

报告地点：js33333金沙线路检测 青岛校区振声苑南楼s204

 

 

摘要：

Understanding human mobility has many applications in diverse areas, including spread of diseases, city planning, traffic engineering, financial market forecasting, and nowcasting of economic well-being. In the past years, we have studied problems concerning the use of various sources of large-scale data to better inform human mobility and collective travel behavior in cities. In this presentation, I will introduce two main works on the applications of human mobility: traffic demand management and the Electric Vehicles charging planning. In the first task, our target is to understand the impact of mega events using multiple data resources and design feasible travel demand management strategy for a global mitigation of traffic congestion. In the second one, we simulate the travel behavior of more than 500 million population in San Francisco Bay Area in USA, and assign each vehicle driver a probability of using EV. Then we couple the urban mobility with EV charging plan to alleviate the pressure of power grid from the EV charging. Finally, we shift the arrival and departure times of EV drivers to reduce the peak load of EV energy demand in the working area.

 

报告人简介：

Yanyan Xu is a postdoctoral associate in the Human Mobility and Networks Lab, Department of Civil and Environmental Engineering, MIT. He is also a visiting scholar at the Department of City and Regional Planning, University of California, Berkeley. He received PhD in Pattern Recognition and Intelligent Systems from Shanghai Jiao Tong University, China, in 2015. He works in the fields of data mining, human mobility, with a focus on the use of information and communication technology and big data in City problems, including Transportation Systems, Environment, and Urban Planning. Specific projects include urban traffic flow prediction, travel demand management using big data; measuring the air pollution exposure with mobile phone data; and coupling electric vehicle charging with urban mobility, etc. His work has been published in the J. Roy. Soc. Interface, IEEE Trans. ITS, J. Adv. Transp., TRB, among others.