报告题目：From traces to trajectories: How well can we guess activity locations from mobile phone traces?
时间：2015年10月30日（星期五）下午14：00
地点：安中大楼A326
报告人：Cynthia Chen，美国华盛顿大学土木与环境工程系，副教授
报告概要:
Passively generated mobile phone dataset is emerging as a new data source for research in human mobility patterns. Information on individuals’ trajectories is not directly available from such data; they must be inferred. Many questions remain in terms how well we can capture human mobility patterns from these datasets. Only one study has compared the results from a mobile phone dataset to those from the National Household Travel Survey (NHTS), though the comparison is on two different populations and samples. This study is a very first attempt that develops a procedure to generate a simulated mobile phone dataset containing the ground truth information. This procedure can be used by other researchers and practitioners who are interested in using mobile phone data and want to formally evaluate the effectiveness of an algorithm.
To identify activity locations from mobile phone traces, we develop an ensemble of methods: a model-based clustering method to identify clusters, a logistic regression model to distinguish between activity and travel clusters, and a set of behavior-based algorithms to detect types of locations visited. We show that the distribution of the activity locations identified from the simulated mobile phone dataset resembles the ground truth better than the existing studies. For home locations, 70% and 97% of identified homes are within 100 and 1000 m from the truth, respectively. For work places, 65% and 86% of the identified work places are within 100 and 1000 m from the true ones, respectively. These results point to the possibility of using these passively generated mobile phone datasets to supplement or even replace household travel surveys in transportation planning in the future.
嘉宾简介：
Cynthia Chen is an associate professor in the department of civil and environmental engineering at the University of Washington, Seattle. She has over 10 years of independent research experience in analyzing people’s daily activity and travel patterns as well as day-to-day variations to understand how human movements are affected by a host of factors. She has designed and managed large-scale regional surveys and developed individual-based micro-simulation models to predict individual movements with a high spatial and temporal resolution. Her current research lies at the intersection of human mobility patterns and infrastructure systems, viewed from a systems perspective to understand their co-evolution over time. She has published in over 45 peer-reviewed articles in many leading journals in transportation, urban studies, and geography. She is currently an associate editor for Transportation. Her research has been supported by both federal and local agencies including NSF, NIH, DOE, DOT, NIST and regional planning agencies. More information of her research can be found at: http://depts.washington.edu/thinklab/
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