While the compact urban model promises long-term sustainability, it often presents the immediate challenge of severe traffic congestion resulting from the inherent lag in travel behavior adaptation behind rapid land development. This study introduces a dynamic simulation framework, integrating grid-based modeling with macroscopic fundamental diagram analysis to resolve this conflict. We identify an optimal urban form that minimizes average travel time, a critical form that triggers gridlock, and a feasible development intensity range between the two forms. Validation against empirical data confirms the general V-shaped travel time pattern, yet reveals a critical divergence: our simulation captures the immediate “shock state” of rapid densification with a significantly steeper speed decline, whereas empirical observations reflect long-term “equilibrium states” after behavioral adaptation. This gap quantifies the adaptation lag and underscores the need for gradual implementation. . Extending the analysis to environmental effects using a hybrid life-cycle assessment framework, we find that, in 2050 under deep decarbonization scenarios, the well-to-tank (WTT) emissions curve adopts a V-shaped pattern similar to that of the travel time curve, achieving approximately 22% lower WTT emissions at its minimum relative to the high-density extreme, with only a marginal 1.9% increase in total well-to-wheel emissions. The closeness of the emissions and efficiency inflection points signals substantial potential for mobility–environment synergies. In plain English, success in compact cities requires localized calibration, gradual phased densification, and policies to accelerate travel behavior adaptation and sustainable mode shift—turning potential gridlock into a driver of resilient urban growth.
Yang et al. (Mon,) studied this question.