Monthly Archives: August 2016
In making decisions about infrastructure development and resource allocation, city planners rely on models of how people move through their cities, on foot, in cars, and on public transportation. Those models are largely based on surveys of residents’ travel habits.
But conducting surveys and analyzing their results is costly and time consuming: A city might go more than a decade between surveys. And even a broad survey will cover only a tiny fraction of a city’s population.
In the latest issue of the Proceedings of the National Academy of Sciences, researchers from MIT and Ford Motor Company describe a new computational system that uses cellphone location data to infer urban mobility patterns. Applying the system to six weeks of data from residents of the Boston area, the researchers were able to quickly assemble the kind of model of urban mobility patterns that typically takes years to build.
The system holds the promise of not only more accurate and timely data about urban mobility but the ability to quickly determine whether particular attempts to address cities’ transportation needs are working.
“In the U.S., every metropolitan area has an MPO, which is a metropolitan planning organization, and their main job is to use travel surveys to derive the travel demand model, which is their baseline for predicting and forecasting travel demand to build infrastructure,” says Shan Jiang, a postdoc in the Human Mobility and Networks Lab in MIT’s Department of Civil and Environmental Engineering and first author on the new paper. “So our method and model could be the next generation of tools for the planners to plan for the next generation of infrastructure.”
To validate their new system, the researchers compared the model it generated to the model currently used by Boston’s MPO. The two models accorded very well.
“The great advantage of our framework is that it learns mobility features from a large number of users, without having to ask them directly about their mobility choices,” says Marta González, an associate professor of civil and environmental engineering (CEE) at MIT and senior author on the paper. “Based on that, we create individual models to estimate complete daily trajectories of the vast majority of mobile-phone users. Likely, in time, we will see that this brings the comparative advantage of making urban transportation planning faster and smarter and even allows directly communicating recommendations to device users.”
Joining Jiang and González on the paper are Daniele Veneziano, a professor of CEE at MIT; Yingxiang Yang, a graduate student in CEE; Siddharth Gupta, a research assistant in the Human Mobility and Networks Lab, which González leads; and Shounak Athavale, an information technology manager at Ford Motor’s Palo Alto Research and Innovation Center.
Nancy Lynch, the NEC Professor of Software Science and Engineering, has been appointed as associate head of the Department of Electrical Engineering and Computer Science (EECS), effective September 1.
Lynch is known for her fundamental contributions to the foundations of distributed computing. Her work applies a mathematical approach to explore the inherent limits on computability and complexity in distributed systems.
Her best-known research is the “FLP” impossibility result for distributed consensus in the presence of process failures. Other research includes the I/O automata system modeling frameworks. Lynch’s recent work focuses on wireless network algorithms and biological distributed algorithms.
The longtime head of the Theory of Distributed Systems (TDS) research group in the Computer Science and Artificial Intelligence Laboratory (CSAIL), Lynch joined MIT in 1981. She received her BS from Brooklyn College in 1968 and her PhD from MIT in 1972, both in mathematics. Recently, Lynch served as head of CSAIL’s Theory of Computation (TOC) group for several years.
She is also the author of several books and textbooks, including the graduate textbook Distributed Algorithms, considered a standard reference in the field. Lynch has also has co-authored several hundred articles about distributed algorithms and impossibility results, and about formal modeling and verification of distributed systems. She is the recipient of numerous awards, an ACM Fellow, a Fellow of the American Academy of Arts and Sciences, and a member of both the National Academy of Sciences and the National Academy of Engineering.
Lynch succeeds Silvio Micali, the Ford Professor of Computer Science and Engineering, who has served as associate department head since January 2015.
“Silvio brought his characteristic diligence and energy to all aspects of his work as department head,” said Anantha Chandrakasan, EECS department head and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “I would like to extend my sincere thanks and express my appreciation for his tremendous service.”