Decision-making game model for urban road network control under oversaturated conditions

Aiming at the difficulty of traffic congestion governance in urban road networks under oversaturated conditions, where traditional traffic control methods have limited effects, this study constructs a decision-making interaction model between traffic management departments and travelers from the perspective of game theory, and explores road network control strategies under different decision-making scenarios. By establishing two types of game frameworks: centralized decision-making and decentralized decision-making (including management-dominated Stackelberg game, traveler-dominated Stackelberg game, and Nash game), the study deduces and comparatively analyzes the control strategies and route selection rules under different models. The research results show that: under the centralized decision-making scenario, the management department and travelers can collaboratively achieve the goal of optimal overall road network efficiency; the proportional relationship between the management department's control cost and travelers' detour cost directly affects the strategy selection of both parties; improving travelers' sensitivity to control measures and optimizing the control cost coefficient can effectively promote the alleviation of road network congestion.