Executive Summary

These days, a large number of vehicles are equipped with GPS devices, and these devices generate huge volumes of trace data. Information extracted from these traces could significantly help transportation planners with routine tasks and special studies. However, extracting information from trace data is a challenging problem because of the proliferation of GPS devices and the rate at which trace data is generated. The proposed research investigates methods to effectively extract accurate and timely information from large volumes of GPS trace data. The specific tasks which will be considered during the 2012 calendar year are as follows.

Task 1: Develop efficient techniques for compressing and storing multiple GPS traces. Such compression techniques must ensure that (i) the resulting representation uses significantly less storage than the original traces, (ii) the information loss due to compression is as small as possible and (iii) the query processing algorithms that extract information from the compressed representation are not adversely affected.

Task 2: Develop a language framework that can be used to express queries on compressed traces and identify techniques to process such queries efficiently. An important goal here is that the framework must facilitate the formulation of queries that are beneficial to transportation planners. Further, query processing algorithms must exploit the compressed representation of the traces.

Potential long term benefits of the proposed research include the development of effective methods for storing large volumes of trace data and new software tools that can be used by transportation planners to obtain information from the trace data.

The deliverables of this project include software tools, research reports, papers submitted to conferences/journals, a research brief suitable for distribution to policy makers and data sets generated as part of the work. These deliverables will be made available to the research community through an appropriate website.

The research team consists of a faculty member (Dr. Lawson) from the Department of Geography and Planning and two faculty members (Dr. Hwang and Dr. Ravi) from the Department of Computer Science. The areas of expertise of these researchers include geographic information systems (GIS), various aspects of transportation, data mining, real-time data stream processing, algorithm design and software system development. Members of this team and their graduate students have been working together on research problems involving GPS trace data since 2009. During the calendar year 2010, the team was supported by a UTRC grant to study techniques for compressing individual GPS traces. The work discussed in this proposal is a natural extension of the previous work.

This project was cosponsored by the Research and Innovative Technology Administration of the U.S. Department of Transportation through the University Transportation Centers program.