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

为了更有效地管理交通网络，智能交通系统(ITS)的发展引起了人们的极大关注。特别是，正在开发先进的旅客信息系统(ATIS)，以实时提醒司机和公共交通乘客延误，以便他们做出旅行决策，以避免拥堵，并利用未充分利用的设施。城市地区的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更好的公共资金投资。这一合作研究项目将通过整合地理学理论和交通网络模型，并明确考虑出行公众空间知识的异质性，开发交通模型来支持这些类型的分析。该研究计划包括建立空间关系测试的实地实验。许多大都会地区的居民将参与有关交通行为、空间知识评估和对交通替代方案的看法的调查。潜在变量和离散选择模型将被估计，以确定交通网络和信息处理能力的知识对短途和长途交通和城市行为的影响。分析将把这些模型的预测能力与传统模型进行比较。这一研究项目的预期结果是增强了对旅行者对新兴信息战略的反应进行建模的能力，以管理交通需求。该项目代表着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他们的空间知识的方法，但这些方法还没有被用来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，而是假设出行者拥有关于网络的完整信息或同质感知误差。更具创新性的研究探讨了空间知识如何影响旅行者对ATIS信息的反应，但没有解决旅行者如何知道替代路线、方式、目的地等更基本的问题。这个项目将通过将空间知识与各种选择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型，从而使政府规划者能够审查交通投资并更有效地分配公共支出。

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.