Cross-domain traffic hysteresis and stability transitions in mixed traffic flow under cognitive uncertainty dynamics

Shuaiyang Jiao, Aizeng Li, Weizhe Meng, Qizheng Pei and Pei Jin

Chaos, Solitons & Fractals, 2026, vol. 208, issue P1

Abstract: To overcome the limitations of the decoupled lateral-longitudinal dynamics assumption in traditional models, this study proposes an entropy-coupled car-following model that combines Bayesian intent inference with cognitive uncertainty. By employing a mean-field approximation, we model lateral disturbances from human-driven vehicles in adjacent lanes as a stochastic environmental field. The core contribution lies in introducing an entropy relaxation mechanism to characterize the perception of lateral intent uncertainty by connected autonomous vehicles (CAVs) and constructing a nonlinear feedback mechanism based on a smooth acceleration saturation function. Stability analysis and numerical simulations show that high-intensity intent uncertainty induces traffic hysteresis and leads to a decline in capacity. Phase transition analysis reveals that the hesitant start mechanism modeled by the smooth saturation function causes the actual critical point of macroscopic traffic breakdown to deviate from the linear theoretical prediction, exhibiting a stabilization effect. Finally, a comprehensive sensitivity analysis of control gain attenuation, acceleration constraints, and entropy relaxation time reveals their nonlinear regulatory mechanisms on system stability. In particular, the study confirms that introducing moderate historical information buffering into the CAV control system can effectively suppress traffic congestion. These findings provide a new perspective for designing robust CAV control systems.

Keywords: Mixed traffic flow; Cognitive uncertainty dynamics; Entropy relaxation; Traffic hysteresis; Phase transition; Cross-domain coupling; Nonlinear stability (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:208:y:2026:i:p1:s0960077926002110

DOI: 10.1016/j.chaos.2026.118070

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