This review explores the potential of digital twin systems to provide a more holistic representation of travel behavior and support transportation planning and policymaking. The paper introduces the concept of digital twins, their key characteristics, and their applications in various domains, including transportation. It discusses the traditional methods used in travel behavior analysis and their limitations, as well as the potential advantages of digital twin systems, such as the integration of heterogeneous data sources, real-time monitoring and prediction, and the ability to simulate and evaluate various policy scenarios. The review also identifies the key components of digital twin systems, the challenges associated with their implementation, and the current state of research on digital twins and related methods in travel behavior analysis. The paper highlights research gaps and future directions, emphasizing the need for privacy-preserving techniques, real-world case studies, and the integration of digital twins with decision support systems. Finally, the review discusses the broader implications of digital twin systems for transportation planning and policymaking, concluding by emphasizing the need for interdisciplinary collaboration and stakeholder engagement to fully realize the potential of digital twins in analyzing travel behavior decisions and shaping the future of transportation systems.

中文翻译：

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数字孪生系统在分析出行行为决策方面的潜力


本综述探讨了数字孪生系统在提供更全面的出行行为表示并支持交通规划和政策制定方面的潜力。本白皮书介绍了数字孪生的概念、它们的关键特性及其在包括交通在内的各个领域的应用。它讨论了出行行为分析中使用的传统方法及其局限性，以及数字孪生系统的潜在优势，例如异构数据源的集成、实时监测和预测，以及模拟和评估各种政策场景的能力。该综述还确定了数字孪生系统的关键组成部分、与其实施相关的挑战，以及数字孪生和出行行为分析中相关方法的研究现状。本文强调了研究差距和未来方向，强调了对隐私保护技术、真实案例研究以及数字孪生与决策支持系统集成的需求。最后，该综述讨论了数字孪生系统对交通规划和政策制定的更广泛影响，最后强调了跨学科合作和利益相关者参与的必要性，以充分实现数字孪生在分析出行行为决策和塑造交通系统未来方面的潜力。