关键词: 城市交通, 时空相关性, 相关性分析, 交通拥堵, 拥堵扩散

Abstract:

The formation and dissipation processes of urban traffic congestions are influenced by shocking waves of different cycles inside the traffic flow. The original factors that lead to traffic congestions are very complicated, the modelling is therefore difficult. This is the main reason that research works about the spatiotemporal dissipation effects for congestions are eventually stopped at the level of qualitative analysis. Some quantitative analysis can be successfully done based on the measured traffic data. However, rare effective knowledge extraction methods can be found to deal with data containing information about multiple time scales and granularities, which however is important to correlation analysis and the direct use of original data leads to unstationary signal features and opposite observation conclusions when putting the data into the discussion of given time scales. Focused on the analysis of spatio-temporal correlation of traffic parameters in congestion areas, a new analyzing method is developed and used based on Pearson's correlation index, which decomposes a measured road speed trajectory into trend and detail components in different time scales. The initial verification and application of this method and the corresponding data segmentation algorithm show the quantitative characteristics of the congestion diffusion in time and space by observing the variation of correlation status.

Key words: urban traffic, spatio- temporal correlation, correlation analysis, traffic congestion, congestion diffusion