While traveling on the road, vehicles often encounter sections where different traffic streams converge due to the geometric design of the roadway. These sections require quick decision-making to ensure smooth driving, making vehicle interactions inevitable, which can lead to safety issues. Therefore, it is important to identify in advance the sections where mandatory lane-changing occurs and to understand the decision-making of the vehicles clearly. This study examines two representative sections where mandatory lane-changing occurs, namely merging sections and roundabouts, and proposes a game-theoretic model to determine the vehicle’s strategy by considering probabilistic payoffs. To this end, this study defined the payoff for decisions as the minimization of travel time or passing time and formalizes the game through a payoff function and matrix. A feasible numerical range is then defined to calculate the probabilities of various driving states on the road, and each equilibrium is evaluated for each situation. Finally, an empirical analysis was performed using large-scale aerial image-based trajectory data, and the predicted results were compared with actual decisions. The model verification showed that the predicted results were highly accurate compared to actual decisions. This study provides a micro-level exploration of lane-changing behavior, allowing for a realistic understanding of decision-making.