Skip to main content


Project Type
UTRC Research Initiative
Project Dates
03/01/2014 - 05/31/2015
Project Status

Nowadays, GPS devices are routinely installed in motorized vehicles. These devices generate huge volumes of trace (or trajectory) data, with each trace giving the position (latitude and longitude) of a vehicle over time. GPS traces contain information that is valuable to many stakeholders such as transportation planners, policy analysts and business organizations (e.g. trucking industry and taxi companies). Such traces are often compressed to eliminate redundancy and reduce the amount of storage space. When additional data about vehicles (e.g. freight information and readings from on- board sensors for trucks, fare and occupancy information for taxicabs) is available, the combination of compressed trace data and vehicular data serves as a richer source of information that is useful in multiple application scenarios. The proposed research investigates methods to e ectively extract information from large volumes of compressed GPS traces and other vehicular data. The speci c tasks which will be carried out during this work are as follows:

Task 1: Develop ecient techniques for retrieving from a database of compressed traces, a collection of traces that are similar to a given query trace. Such techniques should also have the capability to classify the retrieved collection of traces according to speci ed criteria.

Task 2: Extend compression techniques for GPS traces so that traces that include other vehicular or sensor data (along with latitude, longitude and time) can also be e ectively compressed. As in Task 1, such extensions should allow ecient retrievals of collections of traces that are similar to a given query trace.

The proposed work falls under Focus Area 4 ("System modernization through implementation of advanced information technologies") of UTRC Region 2. Potential long term bene ts of the proposed research include the development of e ective methods for extracting useful information from compressed representations of trajectories and other vehicular data. Such methods will be highly bene cial in processing complex queries that are of interest to transportation planners and other stakeholders. The deliverables of this project include software tools, research reports, papers in 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.