SWUTC Research Project Description
Title of Project: ITS Data Compression by Using Advanced Signal Processing Techniques
Project Number: 167651
Principal Investigator:
Fengziang Qiao
(713) 313-1915
P.I. Affiliation: Texas Southern University
Project Monitor:
Andrew C. Mao
Houston TranStar
(713) 881-3170
Project Status: Active
Date Started: 9/1/04
Estimation Completion Date: 8/31/05
Estimated Cost - Current Fiscal: $55,200
Estimated Cost - Total Planned: $55,200
Project Summary:
Project Abstract:
It is very expensive and difficult to store and manage ITS data in a way that can meet a variety of needs and applications. Some current data archiving systems have been developed to deal with the massive amount of data collected from Traffic Management Centers (TMCs). However in most of times, the data are still too huge to be well organized, managed, archived, and smoothly used by the end users. It is very necessary to develop sophisticated approaches to process, manage, and archive ITS data. Effective data compression is one of them. Based on the theory of single processing, the real time ITS data sets can be decomposed into different components. As long as the characteristics of these components are properly stored, the original signal (ITS data set) can be accurately approximated. In this project, the advanced signal procession techniques (e.g. Wavelet Transformation, Fast Fourier Transformation) will be used to decompose and compress the ITS data set. The signal will subsequently be recovered by adequate reconstruction algorithms. Computer software coded in the computer language MATLAB will be developed with suitable Graphic User Interfaces (GUI) designed. The efficiency of the proposed ITS data compression approaches will be examined through the case study in suitable test beds such as San Antonio TransGuide. Conclusions and recommendations will be provided in the final report.
Project Objectives:
The goal of this research is to attempt a way to compress the massive ITS data by using the advanced signal processing approaches. To achieve this objective, the research will:
Task Descriptions:
Task 1: Conduct Literature Search and Develop the Analytical Framework:
The literature review will focus on the state-of-the-art/practice on data compression via signal processing approaches. Literature will be found through scientific papers, reports and websites. Besides, the analytical framework for ITS data compression will be proposed.
Task 2: Identify the Proper Methodologies:
This task will identify the proper methodologies that are suitable for the compression of massive ITS data. The identified methodologies should achieve high performance efficiency, be unproblematic to implement. The compressed signals should be effortlessly recovered, or reconstructed. Possible candidate methodologies include Discrete / Fast Fourier Transformation, Wavelet Transformation, Wavelet Decomposition and Data Compression.
Task 3: Select a Test Bed and Retrieve the Real Time ITS Data:
The research team will make a selection of one or two tested areas in Texas or other states, where the on-line real time ITS data can be easily obtained. One of the possible candidates is San Antonio TransGuide, where on-line ITS data is always available to access. After selected the test bed, the research team will retrieve the real time ITS data and store them in a well-organized database for the consequent decomposition analysis.
Task 4: Develop Corresponding Software:
The corresponding software that can realize the process of ITS data decompression will be developed. The software is to be compiled in the computer language MATLAB with its relevant toolboxes being employed. Graphical User Interfaces (GUI) will be used if possible so that the users could better utilize them.
Task 5: Compress the Retrieved ITS Data Using the Signal Processing Approaches:
The retrieved ITS data from test bed will be compressed using the software developed in Task 4. Possible modifications of the software might be possible depending on the identified problems. This task also includes the reconstruction of the compressed signals to the original signals.
Task 6: Analyze the Efficiency of ITS Data Compression:
For each of the test of different ITS data sets, the efficiency will be analyzed and compared. At least two indexes should be evaluated: compression rate and similarity between original signals and the reconstructed signals. Discussions on the impacts of possible factors that would affect these indexes should be carried out and recommendations to the users proposed.
Task 7: Document Research Results and Findings:
This task will document all research results and findings from this project. A comprehensive final report summarizing the process of ITS data compressions will be delivered.
Index Terms:
Intelligent Transportation Systems; Data Storage; Data Compression; Data Collection; Data Processing; Signal Processing; Fast Fourier Transforms; Wavelets; Computer Programs; Graphic User Interfaces