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<p>In real traffic environments, drivers typically observe surrounding conditions and anticipate upcoming situations, adjusting their behavior accordingly. This anticipatory action, known as the driver anticipation effect, plays a crucial role in traffic. However, its influence on multi-lane traffic with passing behavior has been largely neglected. To address this gap, this study extends the lattice hydrodynamic model to investigate how the driver anticipation affects the stability of multi-lane traffic with the passing behavior. Through the linear and nonlinear analyses, traffic states are categorized into the stable, metastable and unstable states. The theoretical analysis results are verified via the numerical simulations under the periodic boundary conditions. Under a low passing rate, increasing either the anticipation strength or the number of lanes can improve the stability of traffic flow on multi-lane highways. In contrast, once the passing rate exceeds a threshold, the traffic state transitions into a chaotic state. In addition, the power spectrum and spectral entropy analyses show that, at a low passing rate, higher anticipation coefficients and more lanes suppress high-frequency components, resulting in narrower spectra and reduced spectral entropy. In contrast, higher passing rates amplify high-frequency components, leading to an increase in spectral entropy.</p>

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Phase transitions and chaotic jam in multi-lane lattice hydrodynamic model considering driver anticipation and passing behavior

  • 期刊论文

  • 发表日期：

    2026年3月16日

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  • Ronghan Yao,
  • Yanfeng Qiao,
  • Yu Xue,
  • Baofeng Pan,
  • Wensong Zhang

摘要

In real traffic environments, drivers typically observe surrounding conditions and anticipate upcoming situations, adjusting their behavior accordingly. This anticipatory action, known as the driver anticipation effect, plays a crucial role in traffic. However, its influence on multi-lane traffic with passing behavior has been largely neglected. To address this gap, this study extends the lattice hydrodynamic model to investigate how the driver anticipation affects the stability of multi-lane traffic with the passing behavior. Through the linear and nonlinear analyses, traffic states are categorized into the stable, metastable and unstable states. The theoretical analysis results are verified via the numerical simulations under the periodic boundary conditions. Under a low passing rate, increasing either the anticipation strength or the number of lanes can improve the stability of traffic flow on multi-lane highways. In contrast, once the passing rate exceeds a threshold, the traffic state transitions into a chaotic state. In addition, the power spectrum and spectral entropy analyses show that, at a low passing rate, higher anticipation coefficients and more lanes suppress high-frequency components, resulting in narrower spectra and reduced spectral entropy. In contrast, higher passing rates amplify high-frequency components, leading to an increase in spectral entropy.