Toward More Reliable Mobility: Improved Decision Support Tools for Transportation Systems

该项目旨在将出行可靠性集成到交通网络分析方法中，通过开发一个连贯的理论和方法框架来表示网络模型中的出行可靠性，将其纳入网络路线和分配公式，并设计相关的求解算法。在不确定条件下运输系统分析中的几个基本问题将被讨论。首先，研究小组将应用经济学和金融学中成熟的随机支配概念来模拟路线选择中的异质冒险行为，这有望澄清不同风险建模工具之间的联系，并建立更统一的方法来模拟路线选择中的冒险行为。其次，将开发理论上合理的和观测验证的随机性能模型来描述和预测行程时间分布。特别是，将设计新的路线算法来计算和排序先验路线上的旅行时间分布。第三，该项目将创建新的网络模型，能够评估旅行的可靠性，并在多个决策层面上评估其影响。最后，这项研究将阐明如何将出行可靠性信息提供和交通动态纳入基于可靠性的网络模型。将进行使用真实数据构建的案例研究，以评估如何使用这些新模型来预测未来的系统性能，从而支持对旅行可靠性敏感的规划和业务决策。城市交通系统受到各种不确定性的影响，如事故、极端天气、人为灾害、特殊事件和随机出行和活动行为。这些因素单独或结合在一起，可能会对运输服务质量产生不利影响和干扰。特别是，出行行为研究人员已经证实，在高速公路上意外的长时间延误通常会让驾车者产生比“可预测的”更严重的挫折感。因此，将出行可靠性纳入交通网络分析方法是推动这项研究的一个紧迫挑战。在这个项目下产生的建模工具能够考虑旅行时间的不可靠性，它对旅行者如何做出旅行决定(路线、出发时间、方式等)的影响，以及对交通基础设施的整体性能和服务质量的影响。最终，这项研究将通过更好地利用时间和更有效地参与和安排活动，为增强城市流动性和改善生活质量做出贡献。这项研究的成果将通过不同形式(课程开发、教学工具、案例研究等)整合到教学中。从而为未来交通运输劳动力的培训做出贡献。通过这一项目，将开发一个基于网络的可靠路线指南应用程序，并向其他研究人员和公众提供。潜在地，这一工具将使众多驾车者和货运人员受益，并提高公众对旅行可靠性问题的认识。

This project aims to integrate travel reliability into transportation network analysis methods by developing a coherent theoretical and methodological framework for representing travel reliability in network models, incorporating it in network routing and assignment formulations, and devising associated solution algorithms. Several fundamental issues in transportation system analysis under uncertainty will be addressed. First, the research team will apply the concept of stochastic dominance, a well-developed theory in economics and finance, to model heterogeneous risk-taking behavior in route choice, which promises to clarify the connections among different risk-modeling tools and to establish a more unified approach to model risk-taking behavior in route choice. Secondly, theoretically-justified and observationally-validated stochastic performance models will be developed to describe and predict travel time distributions. In particular, novel routing algorithms will be designed to compute and rank travel time distributions on a priori routes. Thirdly, the project will create novel network models capable of assessing travel reliability and evaluating its impacts at multiple levels of decision-making. Finally, the research will shed light on how the travel reliability information provision and traffic dynamics can be incorporated in reliability-based network models. Case studies constructed using real data will be conducted to assess how these new models can be used to predict future system performance, thereby supporting planning and operations decisions sensitive to travel reliability. Urban transportation systems are affected by uncertainties of various sorts, such as accidents, extreme weather, man-made disasters, special events and random travel and activity behavior. Taken individually or in combination, these factors could adversely affect and perturb the quality of transportation services. In particular, travel behavior researchers have established that unanticipated long delays on highways typically produce much worse frustration among motorists than "predictable" ones. Integrating travel reliability into transportation network analysis methods thus presents a pressing challenge that has motivated this research. Modeling tools produced under this project are able to account for unreliability of travel times, its effect on how travelers make travel decisions (route, departure time, mode, etc.), and the implications for overall performance and service quality of transportation infrastructure. Ultimately, the research will contribute to enhanced urban mobility and better quality of life, through better time use and more efficient activity participation and scheduling. The results from this research will be integrated into teaching through different forms (curriculum development, teaching tools, case studies, etc.) and thereby contribute to the training of future transportation workforce. Through this project, a web-based application of reliable route guidance will be developed and made available to other researchers and the general public. Potentially, this tool will benefit numerous motorists and freight and increase the public awareness on travel reliability issues.