交旅融合下，为提升旅游高峰网约车拼车率、促进绿色出行，需设计兼顾碳减排与供需双方利益的激励机制。鉴于此，聚焦旅游高峰出行需求集中、游客对舒适度要求高的特性，提出基于Stackelberg博弈的动态碳补贴策略。通过构建包含35个节点、60条路段的路网模型，量化分析2、3、4人拼车组的碳减排效益，并考虑乘客舒适度、等待时间及平台收益等多目标建立Stackelberg博弈模型，采用遗传算法求解，得到不同拼车组规模下的碳减排效果、各参与方收益分配方案及拼车决策关键影响因素。研究结果表明，3人拼车组碳减排效果明显优于2和4人组；策略实施后，游客出行成本平均降低约25%，平台收益提升约15%，实现乘客与平台双赢；敏感性分析显示，游客的拼车舒适度系数高于等待忍耐度系数，舒适度成为影响拼车决策的关键；鲁棒性测试说明，模型在旅游高峰期交通流波动场景下稳定性良好，碳减排计算偏差小于5%。由此得出结论：交旅场景中3人拼车是碳减排最优规模，基于碳减排效益的动态补贴策略可有效协调平台与乘客利益，是可持续的激励机制，且推行拼车服务时需将舒适度作为重要考量。

Under transportation-tourism integration, to enhance the carpooling rate of ride-hailing services during tourism peaks and promote green travel, it is essential to design an incentive mechanism that balances carbon reduction with the interests of both supply and demand sides. In view of this, focusing on the characteristics of concentrated travel demand and high passenger comfort requirements during peak tourism periods, this paper proposes a dynamic carbon subsidy strategy based on the Stackelberg Game. By constructing a road network model comprising 35 nodes and 60 links, the paper quantitatively analyzes the carbon reduction benefits of carpooling groups with 2, 3, and 4 passengers. Considering multiple objectives such as passenger comfort, waiting time, and platform revenue, a Stackelberg Game model is established. The model is solved using Genetic Algorithm to determine the carbon emission reduction effects for different carpooling group sizes, revenue distribution schemes among stakeholders, and key influencing factors for carpooling decisions. The results indicate that the carbon reduction effect of 3-passenger carpooling groups significantly outperforms those of 2-passenger and 4-passenger groups. After implementing the strategy, tourists′ travel costs decrease by an average of approximately 25%, while platform revenue increases by about 15%, achieving a win-win situation for passengers and the platform. Sensitivity analysis reveals that passengers′ comfort coefficient in carpooling exceeds their waiting tolerance coefficient, making comfort a critical factor influencing carpooling decisions. Robustness tests demonstrate that the model maintains good stability under fluctuating traffic flow scenarios during tourism peaks, with carbon reduction calculation deviations of less than 5%. The conclusion is drawn that in the scenarios of transportation-tourism integration, 3-passenger carpooling represents the optimal scale for carbon reduction. A dynamic subsidy strategy based on carbon reduction benefits can effectively coordinate the interests of the platform and passengers, serving as a sustainable incentive mechanism. Moreover, comfort should be considered as a crucial factor when promoting carpooling services.