کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
977348 1480168 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic analysis of traffic time series at different temporal scales: A complex networks approach
ترجمه فارسی عنوان
تجزیه و تحلیل پویا از سری زمانی ترافیک در مقیاس های زمانی مختلف: یک رویکرد شبکه های پیچیده
کلمات کلیدی
شبکه های پیچیده دینامیک، سری ترافیک زمان، پیچیدگی، دوره ای
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات فیزیک ریاضی
چکیده انگلیسی


• We measure the complexity of traffic time series at different temporal scales.
• Complex networks are constructed by using the correlation coefficient among days.
• The proper critical threshold of networks is estimated by the derivative of density.
• Some statistical properties of complex networks are analyzed.
• We exploit the periodicity in traffic time series.

The analysis of dynamics in traffic flow is an important step to achieve advanced traffic management and control in Intelligent Transportation System (ITS). Complexity and periodicity are definitely two fundamental properties in traffic dynamics. In this study, we first measure the complexity of traffic flow data by Lempel–Ziv algorithm at different temporal scales, and the data are collected from loop detectors on freeway. Second, to obtain more insight into the complexity and periodicity in traffic time series, we then construct complex networks from traffic time series by considering each day as a cycle and each cycle as a single node. The optimal threshold value of complex networks is estimated by the distribution of density and its derivative. In addition, the complex networks are subsequently analyzed in terms of some statistical properties, such as average path length, clustering coefficient, density, average degree and betweenness. Finally, take 2 min aggregation data as example, we use the correlation coefficient matrix, adjacent matrix and closeness to exploit the periodicity of weekdays and weekends in traffic flow data. The findings in this paper indicate that complex network is a practical tool for exploring dynamics in traffic time series.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physica A: Statistical Mechanics and its Applications - Volume 405, 1 July 2014, Pages 303–315
نویسندگان
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