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

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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.