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Phase transition in heterogeneous traffic streams integrating current optimal flux difference under human-driven and connected autonomous vehicles scenario

Author

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  • Yang, Shuhong
  • Xia, Dongxue
  • Liu, Yuangui
  • Peng, Guanghan

Abstract

The persistent existence of mixed traffic flows—consisting of human-driven vehicles (HDVs) and connected autonomous vehicles (CAVs)—poses a significant challenge for future transportation systems. A fundamental but understudied dimension of this heterogeneity resides in the different capacities of CAVs and HDVs to estimate and respond to real-time traffic flux. Therefore, we in this study propose the current optimal flux difference effect (COFDE) as an innovative parameter, incorporating it into a new lattice hydrodynamic model designed for mixed traffic flows. Through rigorous theoretical analysis—including the derivation of linear stability criteria and the mKdV equation—the influence of COFDE on traffic phase transitions is clarified. Supplementary numerical simulations, utilizing density profiles, limit cycles, and spectral analysis, further confirm these theoretical predictions. The findings reveal that COFDE markedly improves the stability and smoothness of heterogeneous traffic flow, effectively alleviating density oscillations and facilitating the achievement of equilibrium states. Notably, the COFDE associated with CAVs possesses a stronger ability to enhance vehicle stability compared to that of HDVs; Additionally, higher CAV penetration rates further boost the overall stability of the traffic system. This work highlights the vital role of information estimation in future traffic management, providing essential insights into the dynamics of mixed-vehicle scenarios and laying a theoretical foundation for advanced control strategies in intelligent transportation systems.

Suggested Citation

  • Yang, Shuhong & Xia, Dongxue & Liu, Yuangui & Peng, Guanghan, 2026. "Phase transition in heterogeneous traffic streams integrating current optimal flux difference under human-driven and connected autonomous vehicles scenario," Chaos, Solitons & Fractals, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:chsofr:v:203:y:2026:i:c:s0960077925016935
    DOI: 10.1016/j.chaos.2025.117680
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    References listed on IDEAS

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