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【背景】一体化的出行即服务（Mobility as a Service, MaaS）平台能够实现地铁与其他交通方式的无缝衔接，显著提升地铁多模式出行的可达性与便捷性，因此有望减少出行者对小汽车的依赖，进而缓解城市交通拥堵。【目标】以网约车出行为基准，评估MaaS环境下地铁多模式出行对其的替代潜力，并识别影响替代潜力的关键因素。【方法】首先，基于MaaS平台将地铁与常规公交、共享单车、拼车等绿色出行方式进行整合，设计十类地铁多模式出行替代方案，并根据接驳距离对替代方案进行匹配；然后，提出综合考虑经济效益、低碳效益与时间成本的替代方案综合效益计算方法，以评估地铁多模式出行的替代潜力；最后，构建CatBoost机器学习模型预测不同条件下网约车出行的可替代性，并采用累积局部效应图分析其影响因素的非线性作用。【数据】基于上海市网约车出行订单数据进行实证研究。【结果】总体约56%的网约车出行可被地铁多模式出行方案所替代，其中市中心区域的可替代比例最高，可达80%以上；影响网约车出行可替代性的关键因素包括网约车出行距离、时间延误比例、替代方案类别、地铁多模式出行距离以及起终点周边建成环境。【结论】研究证实了在MaaS环境下地铁多模式出行对于减少小汽车依赖性具有较大的潜力，同时为政府进一步优化MaaS系统提供了决策依据，有助于提高城市公共交通的分担率。
Abstract：[Background] An integrated mobility-as-a-service(MaaS) platform facilitates seamless metro-multimodal connections, improving accessibility and reducing reliance on private cars, thereby alleviating urban congestion. [Objective] Using ride-hailing trips as a benchmark, this study assesses the substitution potential of metro-integrated multimodal travel in the MaaS environment. It identifies the key factors influencing this substitution. [Method] First, based on the MaaS platform,the metro system is integrated with green travel modes such as conventional buses, shared bicycles,and ridesplitting to design ten types of metro-integrated multimodal travel substitution schemes,which are then matched to ride-hailing trips according to connection distances. Next, a comprehensive benefit evaluation method is proposed that incorporates economic gains, carbon-reduction benefits, and time costs to assess the substitution potential of metro-integrated multimodal travel. Finally, a CatBoost machine learning model is developed to predict the substitutability of ride-hailing trips under different conditions, and accumulated local effect(ALE) plots are used to explore the nonlinear effects of influencing factors. [Data] Empirical analysis is conducted using ride-hailing order data from Shanghai. [Result] The results show that approximately 56% of ride-hailing trips can be substituted by metro-integrated multimodal travel schemes, with the highest substitutability(exceeding 80%) observed in central urban areas. Key factors affecting ride-hailing substitutability include ride-hailing travel distance, proportion of travel delay, substitution scheme, distance of the metro-integrated multimodal trip, and built-environment characteristics around origins and destinations. [Conclusion] The study confirms the substantial potential of metro-integrated multimodal travel to reduce dependence on private cars in the MaaS environment. It also provides policymakers with evidence-based insights to optimize MaaS systems and increase the share of urban public transportation.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2025.05.006
中图分类号:U293.6
引用信息:
[1]李文翔,刘博,袁炫渝,等.出行即服务环境下地铁多模式出行替代潜力评估[J].交通运输工程与信息学报,2026,24(02):53-66.DOI:10.19961/j.cnki.1672-4747.2025.05.006.
基金信息:
国家自然科学基金项目（72471149）; 教育部人文社会科学研究项目（24YJCZH147）; 上海市哲学社会科学规划青年课题项目（2023ECK003）; 上海市教育委员会“人工智能促进科研范式改革赋能学科跃升计划”专项
2025-05-11
2025
2025-06-18
2026-03-02
2026
1
2025-06-16
2025-06-16
2025-06-16