Kerner Boris S, Klenov Sergey L, Schreckenberg Michael
Daimler AG, GR/PTF, HPC: G021, D-71059 Sindelfingen, Germany.
Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Oct;84(4 Pt 2):046110. doi: 10.1103/PhysRevE.84.046110. Epub 2011 Oct 21.
We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules "acceleration," "deceleration," "randomization," and "motion" of the Nagel-Schreckenberg CA model as well as "overacceleration through lane changing to the faster lane," "comparison of vehicle gap with the synchronization gap," and "speed adaptation within the synchronization gap" of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.
我们提出了一个用于双车道道路的简单元胞自动机(CA)模型,该模型解释了交通拥堵、高速公路通行能力以及同步流的物理原理。该模型由纳格尔 - 施雷肯贝格CA模型的“加速”“减速”“随机化”和“运动”规则,以及克erner三相交通理论的“通过变道到较快车道实现过度加速”“车辆间距与同步间距的比较”和“同步间距内的速度自适应”规则组成。我们表明,CA模型的这几条规则能够恰当地模拟在不同国家多年来测量的交通数据中发现的交通拥堵和高速公路通行能力的基本经验特征,如同步流的特征、同一瓶颈处自发和诱发拥堵的存在,以及交通拥堵和高速公路通行能力的相关概率特征。模型模拟得出的单车数据表明,由于对前车较慢速度的速度自适应与超越这辆较慢车辆之间的时空竞争,同步流首先出现,然后自我维持。我们发现,随机化概率和同步间距对驾驶情况的简单依赖关系的应用,使我们能够解释在实际交通数据中观察到的移动同步流模式的物理原理以及同步流中的挤压效应。