To enhance the resilience of urban road networks under frequent recurrent disturbances such as morning peak commuting congestion, this study develops a dynamic resilience assessment framework from the perspective of land-use mix. The model evaluates network resilience by quantifying performance evolution and recovery capacity during the morning peak from both road segment and node dimensions, using land-use mix entropy to characterize functional complexity. The compounded effects of tidal commuting directions and land-use mix are further investigated. Results indicate clear heterogeneity in degradation and recovery trajectories across different land-use mix levels: segments and nodes in high land-use mix areas exhibit more pronounced performance deterioration and delayed recovery. When high land-use mix areas spatially overlap with predominant commuting directions, performance degradation is further amplified and recovery at the end of the morning peak remains lower, revealing critical resilience weaknesses. Accordingly, a land-use mix-oriented targeted optimization strategy is proposed, which enhances system-level resilience by prioritizing capacity improvements on high land-use mix segments. Simulation results show that the proposed strategy increases the network resilience value by 9.46% compared with the baseline scenario, achieving an improvement 2.3 times that of a random capacity expansion strategy. This study provides quantitative evidence for the linkage between land-use mix and dynamic road-network resilience and offers a spatially informed framework for resilience enhancement under recurrent disturbances.
Feng et al. (Wed,) studied this question.