Theoretical and Empirical Analysis of the Effects of Transit System Operations on Urban Networks

该奖项探讨了一个前提，即最近发展起来的网络基本图（NFD）理论可以扩展到考虑交通系统的运行特征（如公交车频率、站点数量、路线数量）对宏观网络性能指标（如网络容量、平均旅行时间和堵塞概率）的主要影响，以及网络性能对交通运营的影响。为了实现这一目标，研究方法将是将NFD理论与移动瓶颈的交通流理论结合起来，产生拟议的NFD运输理论，并使用经验数据和专门为本项目开发的微观模拟模型来评估其结果。这些经验数据将来自亚特兰大地铁地区，包括来自信号交叉口环路探测器的交通数据，以及来自公交车GPS设备和乘客调查的交通数据。如果成功，该奖项将提高我们对交通系统和交通网络性能之间因果机制的理解。由于传统的旅游预测模型依赖于旅行者的来源地和目的地，因此无法令人满意地解决这一问题，因此这项研究可能具有潜在的变革性。所提出的方法是宏观的，因此不需要微观的旅行模式。虽然现实世界的数据会偏离理论的假设，但通过仔细研究这些偏差如何影响预测以及如何改进这一理论，将获得有价值的见解。该项目将制定减少城市拥堵的战略，同时考虑公共和私人交通替代方案。结果将有利于大城市地区的人口，特别是那些经常居住在依赖过境运输地区的人数不足的群体。主要研究结果将通过研究生课程、网上提供的模拟和分析工具以及为规划机构举办的两个讲习班来传播。

This award explores the premise that the recently developed theory of the Network Fundamental Diagram (NFD) can be extended to account for the main effects that transit systems' operational characteristics (such as bus frequency, number of stops, number of routes) have on macroscopic network performance measures (such as, network capacity, mean travel time and probability of gridlock) and for the effects of network performance on transit operations. To accomplish this, the research approach will be to combine NFD theory with traffic flow theory of moving bottlenecks to produce the proposed NFD-transit theory and evaluate its results using both empirical data and a microscopic simulation model especially developed for this project. The empirical data will come from the metro Atlanta region and includes traffic data from loop detectors at signalized intersections and transit data from buses' GPS devices and ridership surveys.If successful, this award will improve our understanding of the cause-and-effect mechanisms between transit systems and transportation network performance. The research could be potentially transformative since traditional travel forecasting models cannot address this problem satisfactorily because of their reliance on travelers' origins and destinations. The proposed method is macroscopic and therefore does not require microscopic travel patterns. Although it is expected that the real-world data will deviate from the assumptions of the theory, valuable insights will be obtained by carefully studying how these deviations affect predictions and how this theory can be improved. The project will develop urban congestion reduction strategies that consider both public and private transportation alternatives. The results will be beneficial to the population of large urban areas, especially to underrepresented groups who often live in transit-dependent areas. The main findings will be disseminated through graduate-level courses, simulation and analysis tools made available online and through two workshops for planning agencies.