A Geospatial Framework for Dynamic Route Planning Using Congestion Prediction in Transportation Systems

In this proposal, we propose to extend GeoDec, which we originally built as a generic system for decision-making in geospatial environments, to support decision-making in transportation systems with dynamic and real-time data. Towards this end, we need to both conduct fundamental research at the data-tier of GeoDec to design new dynamic index structures and develop new services and interfaces at the integration and presentation tiers of GeoDec to support fusion and querying of real-time data. Consequently, GeoDec can operate as a data-driven spatiotemporal decision-making framework for real-time visualization, monitoring, querying, and analysis of transportation systems. Furthermore, we will develop a novel proof-of concept application, namely dynamic vehicle route planner using congestion prediction, to demonstrate the benefits of our new framework. This application will exploit the real-world California transit data from RIITS (Regional Integration of Intelligent Transportation Systems), and will be released for public use.