Decarbonizing urban bus fleets requires not only replacing conventional vehicles with cleanertechnologies but also attracting indifferent passengers (i.e., gray passengers) who may otherwise choose private cars or ride-sourcing services. This study develops a bi-level framework, using multiobjective optimization and evolutionary game, to analyze the behaviour of gray passengers in the bus fleet transition problem under competing transportation modes. The leader (public authority) selects a policy portfolio (i.e., green fleet support subsidies, non-green fleet penalties, ride-sourcing levies, congestion charges, and carbon pricing policy). In response, gray passengers adjust their modal choices among bus, private car, and ride-sourcing, while the transit operator adjusts the green share of its fleet through lower-level evolutionary preference dynamics. The framework embraces equity considerations by capturing key determinants of passenger choice in mode selection (i.e.,travel time, service frequency, crowding, fare, and ride-comfort attributes such as noise, vibration, thermal comfort, and acceleration harshness). The results show that the optimized policy shifts approximately 59.6% of gray passengers to sustainable urban buses, while 23.9% remain with private cars and 16.5% choose ride-sourcing services. The route-level results reveal substantial heterogeneity, indicating that system-wide policy levies should be complemented by route-sensitive service planning.Sensitivity analyses show that gray-market size primarily affects the magnitude of induced bus demand; congestion charges and ride-sourcing levies should be coordinated to avoid cross-substitution; and green-fleet adoption follows a clear subsidy–cost threshold. The findings suggest that effective transit decarbonization requires an integrated policy design that jointly considers fleet transition, competing mobility services, and adaptive passenger behavior.