A probabilistic-dynamic model of generalized impedance for exploring traffic flow evolution under full-closure expressway expansion

With the sustained global growth of motor vehicle ownership, intensified traffic pressure on expressways has made expansion projects a primary means of maintaining smooth and efficient traffic operations. Among expansion project delivery approaches, full-closure construction, while engineering-efficient, may substantially disrupt network structure, degrade operational performance, and heighten travelers’ perceived risk and uncertainty. Therefore, existing route choice models based on deterministic travel-time impedance struggle to accurately capture traffic flow evolution under such disruption. To address this issue, this study proposes a probabilistic-dynamic impedance model that incorporates congestion probability, defined as a single-threshold exceedance probability based on a lognormal distribution of the Travel Time Index (TTI). A congestion amplification factor is also introduced to characterize the nonlinear influence of speed fluctuations on risk perception. Additionally, we develop a dual-layer generalized framework integrating link impedance with path impedance. At the link level, time cost, energy consumption, and monetary expenses are integrated to construct a multidimensional generalized impedance; at the route level, toll station delays and detour tolerance are incorporated to formulate path-level impedance. All these considerations are embedded into a Logit-based stochastic user equilibrium (SUE) assignment framework to examine the evolution of traffic flows under perception uncertainty. Our empirical study in Beijing-Tianjin-Hebei urban agglomeration, China indicates that the proposed model effectively captures the decline in capacity and the flow redistribution effects caused by full-closure construction, revealing a spatial gradient pattern of “core constraint–upstream diffusion.” The findings provide theoretical support for optimizing traffic organization and proactive management during highway construction periods.