Decoupling promotes cooperation in interdependent taxi-carpooling networks

Abstract

Taxi carpooling is regarded as an effective strategy for alleviating urban traffic congestion, yet its actual adoption rate falls considerably short of expectations. Travelers face a social dilemma: individual rationality favors solo travel as a dominant strategy, whereas collective welfare maximization requires cooperative carpooling. Departing from traditional empirical paradigms, this study reveals the nonlinear evolutionary mechanisms of carpooling behavior from a complex network perspective. An interdependent two-layer supply–demand network model is constructed, where the passenger (demand) layer and the taxi (supply) layer are coupled through probabilistic connections. A Prisoner’s Dilemma game is embedded to simulate strategy evolution, where travelers choose between carpooling (cooperation) and non-carpooling (defection) and update strategies by imitating more successful neighbors. Extensive Monte Carlo simulations reveal an unexpected finding: lower inter-layer connection probabilities, lower connectivity degrees, and lower coupling degrees promote higher carpooling density—a network decoupling effect. When the temptation to defect exceeds a critical threshold (approximately T = 2.5), cooperation collapses regardless of network structure, revealing a nonlinear phase transition. Increased node arrival rates significantly promote cooperation in small- to medium-scale networks through continuous network renewal. These findings provide actionable policy insights for urban transportation managers while contributing to a broader understanding of cooperation dynamics on interdependent networks.