中文摘要：

高速公路交通流演化分形特征的研究有助于深刻理解高速公路交通系统的内在演化规律，为高速公路交通流的预测和控制提供理论依据．本文利用统计学方法和复杂网络可视化技术对高速公路交通流的分形特征进行实证分析．首先，利用重标极差法计算了交通流时间序列的Hurst指数和V统计量，发现不同时间标度下高速公路交通流时间序列的Hurst指数都大于0．5，并且V统计量曲线有上升趋势，说明高速公路交通流时间序列具有自相似性和长程相关性；然后，根据可视算法，将高速公路交通流时间序列转化为复杂网络，计算网络的拓扑参数，发现网络的度分布均呈幂律分布，表明该网络为无标度网络，进一步揭示高速公路交通流时间序列为分形序列．同时发现网络的平均路径长度随网络规模的增大呈对数增长，说明网络具有小世界特征．实证分析的结果对高速公路交通流量预测中时间标度的选择和预测长度的确定有重要的参考价值．本文的研究可以为揭示高速公路交通流演化的复杂性提供新的思路和方法．

英文摘要：

Research on the fractal characteristics of freeway traffic flow evolution is helpful to deeply un- derstand the evolution rule of freeway traffic flow system, which can provide the theoretical foundation for forecasting and controlling freeway traffic flow. In this paper, the statistical approaches and complex network visualization technology are applied to investigate the presence of fractal characteristic in the freeway traffic time series. Firstly, by calculating the Hurst exponent and V-statistic through rescaled range analysis, we find the values of the Hurst exponent are greater than 0. 5, and the V-statistic curve has an upward trend, which indicate that the time series of freeway traffic are fractal with self-similarity and long-range dependence. Then, based on the visibility algorithm, we convert the time series into complex networks and calculate the topology parameter of them, the result further shows that freeway traffic flow time series is fractal sequence. The authors also find the average path length increases with the network scale was logarithmic, which shows that the network has the feature of small- world. Em- pirical analysis results can be used as a very important reference to select the time scale and the length ofpredicting for forecasting and controlling freeway traffic flow. Research results in this paper can provide new ideas and methods for investigating the complexity of freeway traffic flow evolution.