具有随机性的智能驾驶员模型--对交通流振荡的新认识
The Intelligent Driver Model with Stochasticity -- New Insights Into Traffic Flow Oscillations
摘要：
交通流振荡，包括交通波，是一种常见的但不完全理解的拥挤交通的特征。可能的机制包括交通流的不稳定性，无差异区域或有限的人类感知阈值（动作点），以及外部加速度噪声。然而，这些因素在特定情况下的相对重要性仍然不清楚。我们把光到这个问题，通过添加外部噪声和动作点的智能驾驶员模型和其他车辆跟驰模型，从而获得一个极小模型包含所有三个振荡机制。我们分析表明，即使在亚临界制度的线性稳定流（序参量$ε<0$），外部白噪声导致时空速度相关性“预期”的波的线性不稳定的制度。在充分远离阈值的情况下，振幅与$(-ε)^{-0.5}$成比例。通过模拟和比较与实验车队和自行车交通，我们表明，外部噪声和无差异区域的行动点具有基本相同的效果。此外，流动的不稳定性占主导地位的高速公路上的振荡，而外部噪声或行动点占主导地位，在低所需的速度，如汽车城市或自行车交通。对于自行车交通，噪声可以导致充分发展的波，即使是在亚临界状态下的单行交通。
英文摘要：
Traffic flow oscillations, including traffic waves, are a common yet incompletely understood feature of congested traffic. Possible mechanisms include traffic flow instabilities, indifference regions or finite human perception thresholds (action points), and external acceleration noise. However, the relative importance of these factors in a given situation remains unclear. We bring light into this question by adding external noise and action points to the Intelligent Driver Model and other car-following models thereby obtaining a minimal model containing all three oscillation mechanisms. We show analytically that even in the subcritical regime of linearly stable flow (order parameter $ε<0$), external white noise leads to spatiotemporal speed correlations "anticipating" the waves of the linearly unstable regime. Sufficiently far away from the threshold, the amplitude scales with $(-ε)^{-0.5}$. By means of simulations and comparisons with experimental car platoons and bicycle traffic, we show that external noise and indifference regions with action points have essentially equivalent effects. Furthermore, flow instabilities dominate the oscillations on freeways while external noise or action points prevail at low desired speeds such as vehicular city or bicycle traffic. For bicycle traffic, noise can lead to fully developed waves even for single-file traffic in the subcritical regime.
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