Collaborative Research: Individuals' Spatial Abilities and Behavior in Transportation Networks

近年来，智能交通系统（ITS）的发展引起了人们极大的关注，以更有效地管理交通网络。 特别是，正在开发先进的旅行者信息系统（ATIS），以提醒司机和公共交通乘客实时延误，使他们能够做出旅行决定，以避免拥堵和利用未充分利用的设施。 城市地区政府需要评估哪些类型的ATIS最具成本效益，以及其他项目是否可能是公共资金的更好投资。 该合作研究项目将开发交通模型，以支持这些类型的分析，通过整合地理理论和交通网络模型，并明确考虑旅游公众之间的空间知识的异质性。 研究计划包括实地实验，以建立空间关系的测试。 一些大都市地区的居民将参加调查，解决交通行为，空间知识的评估，以及交通替代方案的看法。 将估计潜在变量和离散选择模型，以确定运输网络和信息处理能力的知识对短期和长期运输和城市行为的影响。 分析将比较这些模型与传统模型的预测能力。 本研究项目的预期成果是增强能力，以模拟旅行者的反应，新兴的信息战略，以管理运输需求。 该项目代表了基础科学知识的重要进步，因为它将地理理论与交通规划模型更紧密地联系在一起。 许多地理实验已经建立了通过观察一个人的寻路效率和交通行为来衡量其空间知识的方法，但这些方法尚未用于预测未来的旅行选择。 交通规划模型忽略了空间能力和知识的异质性，而是假设旅行者对网络或同质感知错误有充分的信息。 更多的创新研究探讨了空间知识如何影响旅客对ATIS信息的反应，但还没有解决更基本的问题，即旅客如何意识到替代路线、模式、目的地等。本项目将通过将空间知识与全方位的交通选择联系起来来解决这个问题。 项目结果将有助于完善现有的交通规划模式，从而使政府规划人员能够审查交通投资，更有效地分配公共开支。

Considerable attention has focused recently on the development of Intelligent Transportation Systems (ITS) to more effectively manage transportation networks. In particular, Advanced Traveler Information Systems (ATIS) are being developed to alert drivers and public transportation passengers to delays in real-time so they can make travel decisions to avoid congestion and take advantage of under-utilized facilities. Urban area governments need to assess which types of ATIS are most cost-effective, and whether other projects might be better investments of public funds. This collaborative research project will develop transportation models to support these types of analysis by integrating geographic theories and transportation network models and explicitly considering the heterogeneity of spatial knowledge among the traveling public. The research plan includes field experiments to establish tests of spatial relationships. Residents of a number of metropolitan areas will participate in surveys that address transportation behavior, assessment of spatial knowledge, and perceptions of transportation alternatives. Latent variable and discrete-choice models will be estimated to establish the effect that knowledge of the transportation network and information-processing capabilities have on short- and long-range transportation and urban behaviors. The analysis will compare the predictive capabilities of these models against conventional models. The expected outcome of this research project is an enhanced capability to model travelers' responses to emerging information strategies to manage transportation demands. This project represents an important advance in basic scientific knowledge, as it more closely ties geographic theories to transportation planning models. Many geographic experiments have established means to measure a person's spatial knowledge by observing their wayfinding efficiency and transportation behavior, but these methods have not been used to predict future travel choices. Transportation planning models have ignored the heterogeneity of spatial ability and knowledge and instead assumed that travelers have full information about the network or homogenous perception errors. More innovative research studies have examined how spatial knowledge may influence travelers' response to ATIS messages but have not addressed the more basic question of how travelers become aware of alternative routes, modes, destinations, etc. This project will address that question by relating spatial knowledge to transportation choice from the full range of options. Project findings will contribute to the refinement of existing transportation planning models, thereby allowing government planners to examine transportation investments and more effectively allocate public expenditures.