%0 Journal Article
%T Urban Mobility Dynamics Based on Flexible Discrete Region Partition
%A Liang Wang
%A Kunyuan Hu
%A Tao Ku
%A Junwei Wu
%J International Journal of Distributed Sensor Networks
%D 2014
%I Hindawi Publishing Corporation
%R 10.1155/2014/782649
%X Understanding the urban mobility patterns is essential for the planning and management of public infrastructure and transportation services. In this paper we focus on taxicab moving trajectory records and present a new approach to modeling and analyzing urban mobility dynamics. The proposed method comprises two phases. First, discrete space partition based on flexible grid is developed to divide urban environment into finite nonoverlapping subregions. By integrating mobility origin-destination points with covered region, the partitioned discrete subregions have better spatial semantics scalability. Then, we study mobility activity and its distribution randomness during given time periods among discrete subregions. Moreover, we also carry out the analysis of mobility linkage of mobility trips between different regions by O-D matrix. We present a case study with real dataset of taxicab mobility logs in Shenzhen, China, to demonstrate and evaluate the methodology. The experimental results show that the proposed method outperforms the clustering partition and regular partition methods. 1. Introduction The widespread deployment of location-aware technologies in urban area has led to a massive increase in the volume of movement trace records. By means of these movement trajectories, we can advance our method of urban computing and human behavior analysis. Actually, modeling and analyzing urban mobility through human movement is crucial to traffic forecasting, urban planning, and location based services. In practice, GPS-equipped taxicabs can be viewed as ubiquitous mobile sensors probing a city¡¯s rhythm and pulse. And these taxicab trace records allow for the development of novel way to uncover the underlying human behavior and urban mobility dynamics. However, there are great challenges for the analysis of mobility trajectory due to mixture of temporal and spatial relationship and massive data size. In this paper, we explore the challenges of modeling urban mobility by taxicab moving trajectories. There are two important issues we need to address in order to approach a better understanding of urban mobility dynamics. The first is accurate calculation of urban mobility activity. And the other is analyzing mobility linkage between different regions in urban environment. Based on the proposed flexible discrete region partition method, we calculate urban mobility activity by origin-destination points in taxicabs moving dataset and analyze the activity randomness across different time scales. Moreover, we compute mobility linkages between different urban regions
%U http://www.hindawi.com/journals/ijdsn/2014/782649/