Macroscopic Traffic Flow Modeling Under Heterogeneous Traffic Condition

Abstract:

A modeling method of dynamic graph hybrid automata combined with an improved cell transmission model was proposed. Based on the triangular fundamental diagram fitting results of flow volume and density of road segment under different mixing ratios of automated driving vehicles， the variation rules of critical congestion density， traffic capacity， reverse wave velocity and other main parameters were discussed， and the traditional cell transmission model was improved. The dynamic graph hybrid automata was used to characterize the hierarchical topology of road network， and the improved cell transmission model was embedded into the dynamic graph hybrid automata to establish a macroscopic traffic flow model under heterogeneous traffic condition. Finally， simulation platform was built by using the OpenModelica software to verify the effectiveness of the modeling method. The results show that with the increase of the mixing ratio of automated driving vehicles， the critical congestion density， maximum traffic capacity and reverse wave velocity of road segment all have significant changes.