Bicycle longitudinal elastic cellular automaton model based on behavior characteristics analysis

Abstract

In response to the insufficient consideration of cyclists' behavioral analysis in previous studies, it is proposed that the spatial occupancy of cyclists is not a traditional rectangle but more like a horizontally oriented box plot. The narrower front and rear spatial occupancy allow cyclists to laterally offset slightly while following more closely longitudinally. By discretizing the cellular space and allowing cell overlaps, an improved one-dimensional cellular automaton model is introduced. An elasticity coefficient is introduced to characterize the probability of cyclists choosing to follow closely based on density variations. Comparisons with representative experimental data and existing models demonstrate that the proposed model exhibits higher congestion density and maintains high flow rates even at high densities, aligning more closely with real-world scenarios.