摘要The fundamental diagram is the graphical representation of the relations between traffic flow, speed, and density, and has long been the foundation of traffic flow theory and transportation engineering. Eighty years after the seminal Greenshields model, a variety of models have been proposed to mathematically represent the speed-density relation. Speed-density relation models play an important role in understanding how a shock wave propagates through traffic, as well as determining level of service. In this paper, 10 typical speed-density relation models are summarized and analyzed by parameter calibrations and fitting errors using Beijing Expressway data. The results show that fitting errors for speed-density models are not sensitive to using different sets of field data, whereas some physically meaningful parameters, such as free-flow speed and jam density, vary widely under different sets of field data. The Newell and Logistic models demonstrate good stability. This research provides practical support for optimizing speed-density relation models and model parameter calibration.
Abstract：The fundamental diagram is the graphical representation of the relations between traffic flow, speed, and density, and has long been the foundation of traffic flow theory and transportation engineering. Eighty years after the seminal Greenshields model, a variety of models have been proposed to mathematically represent the speed-density relation. Speed-density relation models play an important role in understanding how a shock wave propagates through traffic, as well as determining level of service. In this paper, 10 typical speed-density relation models are summarized and analyzed by parameter calibrations and fitting errors using Beijing Expressway data. The results show that fitting errors for speed-density models are not sensitive to using different sets of field data, whereas some physically meaningful parameters, such as free-flow speed and jam density, vary widely under different sets of field data. The Newell and Logistic models demonstrate good stability. This research provides practical support for optimizing speed-density relation models and model parameter calibration.
徐程, 曲昭伟, 陈晓明. 交通流速度-密度模型特性分析[J]. Journal of Highway and Transportation Research and Development, 2014, 8(4): 104-110.
XU Cheng, QU Zhao-wei, CHEN Xiao-ming. Analysis of Traffic Flow Speed-density Relation Model Characteristics. Journal of Highway and Transportation Research and Development, 2014, 8(4): 104-110.
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2014, Vol. 8 
