A flexible traffic stream model and its three representations of traffic flow. (February 2017)

• Record Type: Journal Article
• Authors: Zheng, Liang; He, Zhengbing; He, Tian
• Is Part Of: Transportation research. Volume 75(2017)
• Page Start: 136
• Page End: 167
• Publication Date: 2017-02
• Subjects: Traffic stream model -- Car-following model -- Fundamental diagram -- Lagrangian coordinate; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2016.12.006
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: A flexible traffic stream model is proposed from a novel car-following model. Four driving behavior parameters greatly influence the shape of fundamental diagram. This model and related traffic flow phenomena are revisited on Lagrangian coordinates. The model exhibits well flexibility to fit real-field data and are better than others. Macro- and micro-solutions on shockwaves are consistent with each other. Abstract: To connect microscopic driving behaviors with the macro-correspondence (i.e., the fundamental diagram), this study proposes a flexible traffic stream model, which is derived from a novel car-following model under steady-state conditions. Its four driving behavior-related parameters, i.e., reaction time, calmness parameter, speed- and spacing-related sensitivities, have an apparent effect in shaping the fundamental diagram. Its boundary conditions and homogenous case are also analyzed in detail and compared with other two models (i.e., Longitudinal Control Model and Intelligent Driver Model). Especially, these model formulations and properties under Lagrangian coordinates provide a new perspective to revisit the traffic flow and complement with those under Eulerian coordinate. One calibration methodology that incorporates the monkey algorithm with dynamic adaptation is employed to calibrate this model, based on real-field data from a wide range of locations. Results show that this model exhibits the well flexibility to fit these traffic data and performs better than other nine models. Finally, a concrete example of transportation application is designed, in which the impact of three critical parameters on vehicle trajectories and shock waves with three representations (i.e., respectively defined in x - t, n - t and x - n coordinates) is tested, and macro- and micro-solutions on shock waves well agree with each other. In summary, this traffic stream model with the advantages of flexibility and efficiency has the good potential in level of service analysis and transportation planning.