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Mobile apps and wearable devices accurately and continuously measure human activity; patterns within this data can provide a wealth of information applicable to fields such as transportation and health. Despite the potential utility of this…
Discovering human mobility patterns with geo-location data collected from smartphone users has been a hot research topic in recent years. In this paper, we attempt to discover daily mobile patterns based on GPS data. We view this problem…
Human mobility is subject to collective dynamics that are the outcome of numerous individual choices. Smart card data which originated as a means of facilitating automated fare collections has emerged as an invaluable source for analyzing…
Understanding driving behaviors is essential for improving safety and mobility of our transportation systems. Data is usually collected via simulator-based studies or naturalistic driving studies. Those techniques allow for understanding…
Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile…
Many aspects of life are associated with places of human mobility patterns and nowadays we are facing an increase in the pervasiveness of mobile devices these individuals carry. Positioning technologies that serve these devices such as the…
Nowadays, travel surveys provide rich information about urban mobility and commuting patterns. But, at the same time, they have drawbacks: they are static pictures of a dynamic phenomena, are expensive to make, and take prolonged periods of…
Clustering of motion trajectories is highly relevant for human-robot interactions as it allows the anticipation of human motions, fast reaction to those, as well as the recognition of explicit gestures. Further, it allows automated analysis…
We apply a simple clustering algorithm to a large dataset of cellular telecommunication records, reducing the complexity of mobile phone users' full trajectories and allowing for simple statistics to characterize their properties. For the…
Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences…
Human mobility demonstrates a high degree of regularity, which facilitates the discovery of lifestyle profiles. Existing research has yet to fully utilize the regularities embedded in high-order features extracted from human mobility…
The analysis of longitudinal travel data enables investigating how mobility patterns vary across the population and identify the spatial properties thereof. The objective of this study is to identify the extent to which users explore…
Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper…
Human mobility clustering is an important problem for understanding human mobility behaviors (e.g., work and school commutes). Existing methods typically contain two steps: choosing or learning a mobility representation and applying a…
The problem of unicity and reidentifiability of records in large-scale databases has been studied in different contexts and approaches, with focus on preserving privacy or matching records from different data sources. With an increasing…
We introduce a novel statistical framework for analyzing the GPS data of a single individual. Our approach models daily GPS observations as noisy measurements of an underlying random trajectory, enabling the definition of meaningful…
Understanding human mobility is essential for many fields, including transportation planning. Currently, surveys are the primary source for such analysis. However, in the recent past, many researchers have focused on Call Detail Records…
In the era of mobile computing, understanding human mobility patterns is crucial in order to better design protocols and applications. Many studies focus on different aspects of human mobility such as people's points of interests, routes,…
A new generation of "behavior-aware" delay tolerant networks is emerging in what may define future mobile social networks. With the introduction of novel behavior-aware protocols, services and architectures, there is a pressing need to…
Circadian rhythm is the natural biological cycle manifested in human daily routines. A regular and stable rhythm is found to be correlated with good physical and mental health. With the wide adoption of mobile and wearable technology, many…