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

本项目旨在通过开发一个连贯的理论和方法框架，将出行可靠性纳入交通网络分析方法，以表示网络模型中的出行可靠性，将其纳入网络路由和分配公式，并设计相关的解决算法。讨论了不确定条件下运输系统分析中的几个基本问题。首先，研究团队将运用经济学和金融学中较为成熟的随机优势理论对路径选择中的异质性风险行为进行建模，这将有助于澄清不同风险建模工具之间的联系，并建立更统一的路径选择风险行为建模方法。其次，将建立经过理论验证和观测验证的随机性能模型来描述和预测旅行时间分布。特别是，新的路由算法将被设计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，能够评估旅行可靠性，并评估其对多层次决策的影响。最后，研究将揭示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。使用真实数据构建的案例研究将进行，以评估这些新模型如何用于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运营决策。城市交通系统受到各种不确定性因素的影响，如事故、极端天气、人为灾害、特殊事件以及随机的出行和活动行为。单独或综合考虑，这些因素可能对运输服务的质量产生不利影响和扰乱。特别是，旅行行为研究人员已经确定，在高速公路上，意想不到的长时间延误通常比“可预测的”长时间延误更让驾车者感到沮丧。因此，将出行可靠性整合到交通网络分析方法中提出了一个紧迫的挑战，这促使了本研究的开展。在这个项目下产生的建模工具能够解释旅行时间的不可靠性，它对旅行者如何做出旅行决策（路线、出发时间、模式等）的影响，以及对交通基础设施整体性能和服务质量的影响。最终，该研究将有助于通过更好的时间利用和更有效的活动参与和安排，提高城市机动性和生活质量。本研究的结果将通过不同的形式（课程开发、教学工具、案例研究等）整合到教学中，从而有助于培养未来的交通劳动力。通过这个项目，将开发一种基于网络的可靠路线指导应用程序，并向其他研究人员和公众提供。潜在地，这个工具将使许多驾车者和货运受益，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.