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.

拥挤的交通流表现出时空演化的相当复杂的特性，例如停走波，幻影拥塞，流密度数据的广泛散布等。据我们所知，以前在圆形轨道上进行的跟车实验仅进行了大量研究拥塞的流量。仍然缺乏关于轻度拥塞流动的实验研究，轻度拥塞流动表现出与重度拥塞流动不同的稳定性。为了填补这一空白，最近我们在密度为0.049、0.043和0.037 m ^-1的812米圆周电路上进行了大规模的跟车实验。实验的流量-密度关系与经验值高度一致，这表明实验中的驾驶行为与实际交通中的行为类似。通过比较在相同全局密度下不同运行中的宏观时空演化图，我们发现即使在相同初始条件下，交通流也表现出随机特征。我们分析了跟车行为及其与宏观交通流演变的关系。研究发现，冷漠区域，驾驶员的敏感性和随机性强度都有助于宏观交通流的演变模式。具体来说，随着无差异区域的扩大，灵敏度的整体下降和随机性强度的下降，交通流在时空上变得更加均匀。进一步研究了随机性和速度适应性的作用。已经发现，更强的交通振荡对应于更强的随机性和速度适应性。两种效应之间的竞争分析表明，速度适应效应与随机效应之比随振荡幅度的增加而增大。当振荡幅度较小时，随机效应在汽车跟随中起主导作用。随着振荡幅度的增加，它的影响逐渐减弱，速度适应效应的增长超过了随机效应的影响。这些发现有望增进我们对产生轻度拥塞流的时空演化模式的潜在机制的理解，并且本研究中收集的数据可用于测试交通模型和理论。