一体化交通需求管理组合策略作用机制研究

With public regulation, public policy and performance evaluation theories, this project aims to discover how the government intervenes the ownership and usage of automobiles by coordinating the marketing and non-marketing tools to realize Traffic Demand Management(TDM) objectives. .First, based on the circumstance and characteristics of China’s urban traffic management, a series of feasible, comprehensive strategies are put forward to regulate the ownership and usage of automobiles by a large amount of integrated, comparative studies between countries, cities and case studies with SCBA, SWOT methods and multiple dimensions. .Second, a systematic analysis is conducted to evaluate the performance of these comprehensive TDM strategies. It includes: .(1)Micro effects analysis: To the car ownership regulation, an allocation theory of vehicle quota based on multiple objectives auction theory is proposed to match the practice of the auction, ballot and mixed mechanism in China cities today. To the car usage regulation, the individual decision-making process and behavior response to the integrated strategies are carefully studied with Generalized Extreme Value(GEV) models, especially on preference heterogeneity, spatial correlation and income sensitivity while making decision under different policy scenarios. .(2)Meso effects analysis: Stakeholder analysis is developed with multi-agents policy games, including games within and beyond transportation systems, games between central and local governments, games between policy-maker and travelers, and games among heterogeneous travelers, in order to demonstrate the policy-making and implementing mechanism. The decision-making structure of centralization and decentralization on the policy performance are found out and its equilibrium is explained to reflect meso policy effects. .(3) Macro effects analysis: With econometric tools like Difference-in-Difference(DID), Structural Vector Autoregression(SVAR), Propensity Score Matching(PSM) methods, Synthesis Control Methods(SCM) and Regression Discontinuity(RD), empirical studies are performed with the provincial and urban time series and panel data to reveal the macroscopic policy effects. .Finally, with a system dynamics simulation on policy mechanism, a new evaluation theory of transport regulation policy is summarized to systematically describe the performance of comprehensive TDM strategies which will greatly improve the solutions to urban transportation problems in China.

拟运用公共管制、公共政策和绩效评估等理论，研究政府如何通过行政、经济、社会手段的协同作用，对机动车拥有和使用行为进行干预，以实现交通需求管理目标。首先，建立可比性框架，通过多国别、多城市、多案例分析，筛选出符合我国国情、可行优化的一体化TDM组合策略。其次，通过建立机动车拥有环节的额度配置理论，以及机动车使用环节的出行行为广义极值模型来反映管制政策的微观影响。第三，在中观层次上，采用多主体博弈分析，研究不同利益相关者在管制组合策略下的均衡状态，以及集权与分权的决策结构对管制绩效的影响。第四，利用我国城市机动车发展统计数据库，采用DID、SVAR、PSM、SCM、RD等计量分析工具建立时间序列和面板数据模型，评价交通管制政策的宏观效应。最后，在对组合策略的整体政策效果进行系统动力学仿真和综合评价之后，将研究成果予以总结和提升，形成交通管制政策的系统评价理论，为改善城市交通提供可行政策建议。

项目构建一体化交通需求管理（TDM）组合策略干预机动化进程的学理基础，阐明管制措施的宏中微观互动机制，研判组合策略的可行性及其效果，为交通政策制定提供理论参考。.在理论构建方面。（1）以机动车拥有权管制为突破口，构建符合我国国情的机动化干预理论，着重探讨行政干预、市场调节和社会自治相结合的政府管理手段以及可行的管制组合策略。（2）从代表性政策的影响机制出发，聚焦多个政策的联动关系，在微观、中观和宏观层面构建TDM组合策略作用机制理论：建立广义极值模型探讨偏好异质性、空间相关性和收入敏感性等特征对交通需求和政策效应的影响；建立交通系统内外部博弈模型，阐述政策中观形成机制和作用机理；构建系统评价理论体系，对交通管制政策绩效进行综合评价。（3）以“事件-机制-效应”分析为切入点，构建政策动力学分析框架：建立反映宏观政策效应的经济计量模型，验证政策过程中的因果关系；将动力学思想方法运用于政策影响机制，描述政策过程的动态性，揭示政策演化的影响因素。 .在实证分析方面。综合应用多种建模方法、经济计量分析方法和大数据处理方法，对机动化干预效果和组合策略作用机制进行验证，为组合策略的改进方向提供依据。采用探索性因子分析、政策文本分析、群组分析等质性研究方法，多元线性回归、ARIMA、DID、DDD、SVAR、PSM、SCM和DR等计量分析方法，离散选择模型、结构方程模型、扩展博弈模型等评估模型，并运用Bhattacharyya距离、提升决策树及改进拉斯维加斯方法（包裹法）等归纳学习工具进行实证分析。.在案例研究方面。（1）多案例精细度分析：对八个汽车限购省市在历史演化、关键事件、优势劣势等方面展开个案分析，对组合策略的实施效果做出综合评价。（2）多案例群组分析：识别我国298个城市疫情初期交通管控政策类型和影响因素，由117个城市停车政策归纳我国停车市场化改革进程及其特点，对256个地级市网约车监管政策进行类别划分，为数智时代高密度城市机动化管理提供借鉴。

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