Abstract
Congested traffic flow exhibits rather complex properties of spatiotemporal evolution, e.g. stop-and-go waves, phantom jams, wide scattering of flow-density data, etc. To the best of our knowledge, previous car-following experiments on circular tracks only studied heavily congested flow. The experimental study concerning lightly congested flow, which exhibits different stability characteristic from heavily congested flow, is still lacking. To fill this gap, very recently we conducted a large-scale car-following experiment on an 812-meter circumference circuit with densities of 0.049, 0.043 and 0.037 m−1. The flow-density relation of the experiment is highly consistent with the empirical one, which indicates that the driving behavior in the experiment is similar to that in real traffic. By comparing the macroscopic spatiotemporal evolution diagrams in different runs under the same global density, we found that the traffic flow exhibits stochastic features with even the same initial conditions. We analyzed the car-following behavior and its relation to the macroscopic traffic flow evolution. It was found that the indifference region, the sensitivity of drivers, and the strength of stochasticity all contribute to the macroscopic traffic flow evolution pattern. Specifically, the traffic flow becomes more homogeneous in time-space with the expansion of indifference region, the overall decrease of sensitivity and the decrease of stochasticity strength. The roles of stochasticity and speed adaptation were further investigated. It was found that stronger traffic oscillations correspond to stronger stochasticity and speed adaptation. The analysis for competition between the two effects indicated that the ratio between speed adaptation effect and stochastic effect grows with the increase of the oscillation amplitude. The stochastic effect plays a dominant role in car following when the oscillation amplitude is small; its influence wanes and the speed adaptation effect grows to outweigh the influence of the stochastic effect as oscillation amplitude grows. These findings are expected to improve our understanding of the underlying mechanism that produces the spatiotemporal evolution patterns of lightly congested flow and the data collected in this study can be used to test traffic models and theories.
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