Phase transitions in a heterogeneous lattice hydrodynamic model involving both communication distance and memory time duration differences

Guanghan Peng, Wanlin Wang and Huili Tan

Chaos, Solitons & Fractals, 2024, vol. 188, issue C

Abstract: An in-depth analysis of vehicle heterogeneity characteristics in intelligent heterogeneous traffic flows, involving connected autonomous vehicles and human-driven vehicles, is essential to reveal the evolutionary mechanism of congestion and to understand its interaction among traffic factors. It has significant theoretical value in guiding the future field deployment and testing of large-scale connected autonomous vehicles through the systematic analysis of the complex dynamic characteristics of intelligent heterogeneous traffic flows from a traffic engineering perspective, as well as traffic management and control in intelligent heterogeneous traffic flow environments. In this study, the lattice hydrodynamics model is applied to construct a corresponding traffic flow model for the differences of communication capability and historical information memory capability for heterogeneous vehicles. The roles of these heterogeneous properties and their interactions are investigated. Through linear stability analysis and nonlinear analysis, we in this study explore the influence of key traffic factors involving the differences of communication capability and historical information memory capability contributing to ameliorating intelligent heterogeneous traffic dynamics, and numerical simulations are carried out to verify the accuracy and reliability of theoretical analysis. An interesting discovery is that longer memory duration gets better, but the optimizing impact of memory duration on the system being marginally decreasing.

Keywords: Heterogeneous traffic flow; Lattice hydrodynamic model; Communication distance; Historical information memory time (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:188:y:2024:i:c:s0960077924010543

DOI: 10.1016/j.chaos.2024.115502

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