CAREER: The Evolution of Transportation Networks: Empirical Research and Agent-Based Models

摘要摘要-职业生涯：交通网络的演化：实证研究和基于代理的模型本研究试图在理论和实证层面上理解交通网络的演化增长过程，认识到供给和需求的相互依赖性。需要研究的关键问题包括：为什么网络会扩张和收缩？网络会自我组织成层级结构吗？道路（路线）是网络的一种紧急属性吗？什么投资规则预测网络改进的顺序和位置？什么时候扩建现有的设施（在同一条线路上增加更多的车道），而不是提供新的设施（一条新的线路）？如何改进交通规划，以利用对网络演变的新认识？据推测，简单的，可测量的因素（如交通增长率，容量比，并与相邻的上游和下游链路的比较）解释了许多由此产生的决定。这项调查将研究明尼阿波利斯和圣保罗双城的资本改善项目和决策的时间序列，将它们与网络结构特征。这些经验模型将嵌入基于代理的模型，以复制网络的growth.This研究指定和估计组件模型解释出行行为，网络成本和收入，以及投资决策的过程。然后将这些组件集成到仿真模型中并进行测试。对单个组件模型的估计以及将其集成到网络增长（和下降）的模拟中，将增加我们对网络演化过程的有限理解。这种新的认识将对交通规划实践产生更广泛的影响，并最终影响城市和地区的形态。在决策过程中明确网络外部性的度量将导致更好的计划、网络路由决策和实施策略。理解和说明一个时间点的决策如何影响未来的选择，应有助于指导规划者和决策者希望塑造未来。将评估渐进变化的长期后果。这将有助于决策者评估扩大现有设施或路线，或建立新的通行权或提供新服务的影响。这种对长期网络动态的更好理解将导致更好的道路网络规划和设计，以利用网络外部性并最大限度地为决策者提供未来选择。本研究的主要教育目标是：（1）将交通网络的演变融入城市交通规划、交通经济学、交通与土地利用等课程中，（二）开发一个关于交通政策的新生研讨会，通过本科生研究机会让明尼苏达大学的本科生参与进来计划，和3）涉及美国土著高中学生从丰迪拉克部落在运输。在课程中使用模拟模型将为学生提供一个独特的工具，用于理解网络演变的政策决策的影响。

AbstractAbstract - CAREER: The Evolution of Transportation Networks: Empirical Research and Agent-Based ModelsThis research endeavors to understand the evolutionary growth process of transportation networks at a theoretical and empirical level, recognizing the inter-dependence of supply and demand. Key questions to be examined include: Why do networks expand and contract? Do networks self-organize into hierarchies? Are roads (routes) an emergent property of networks? What investment rules predict the sequence and location of network improvements? When are already existing facilities expanded (more lanes on the same link) as opposed to new facilities being provided (a new link)? How can transportation planning be improved to take advantage of a new understanding of network evolution?It is hypothesized that simple, measurable factors (such as traffic growth rates, volume to capacity ratios, and comparison with adjacent upstream and downstream links) explain many of the resulting decisions. This investigation will examine a time series of capital improvement projects and decisions for the Twin Cities of Minneapolis and St. Paul, relating them to network structure characteristics. These empirical models will be embedded in agent based models to replicate the process of network growth.This research specifies and estimates component models explaining travel behavior, network costs and revenue, and investment decisions. Then the components will be integrated into the simulation model and tested. Both the estimation of individual component models and their integration into a simulation of network growth (and decline) will increase our limited understanding of network evolution processes. This new understanding will have broader impacts on transportation planning practice, and ultimately on the shape of cities and regions. Incorporating explicit measures of network externalities in decision making will lead to better plans, network routing decisions, and implementation strategies. Understanding and illustrating how decisions in one point of time affect future choices should help guide planners and decision-makers desiring to shape the future. The long-term consequences of incremental changes will be assessed. This will help decision-makers assess the effects of expanding existing facilities or routes, or building in new rights-of-way or offering new services. This improved understanding of long term network dynamics would lead to better planning and design of road networks to exploit network externalities and maximize future choice for decision makers. The knowledge of how current decisions foreclose or create future opportunities should improve decision-making.The primary educational objectives of the research are to 1) integrate transportation network evolution into courses on Urban Transportation Planning, Transportation Economics, and Transportation and Land Use, 2) develop a Freshman Seminar on Transportation Policy to involve University of Minnesota undergraduates through the Undergraduate Research Opportunities Program, and 3) involve Native American High School Students from the Fond du Lac tribe in Transportation. Use of the simulation model in the courses will provide the students a unique tool for understanding the implications of policy decisions on network evolution.