Virtual Environment for Transportation Data

Contact:  R. Gordon McKeen, P.E.

The objective of this project was to develop prototype software to demonstrate the concept of a virtual environment transportation data (VETD) management system. The VETD management software demonstrated how available transportation/highway data could be made more accessible to the transportation/highway engineer by making them easier to use through a virtual reality environment. The project involved Dr. Koon Meng Chua, Civil Engineering Department; Dr. George Luger, Computer Science Department; and John Burge, a graduate student in Computer Science.

As more and more data are collected by highway departments and stored in single or multiple databases, there will come a point where the traffic and the highway engineer will be so overwhelmed that they will seek the minimal and most easily accessible data that could be used in their work. Therefore, in order for the massive amount of data collected to remain useful to these engineers, there is a need for a computerized system that has specifc features. These features are: (1) a quick way to determine what data is available, (2) an easy method of retrieving relevant data, (3) a method of visualizing the retrieved data, (4) a method of analyzing the data using a statistical package or pattern recognition, (5) a method of visualizing the site from the birds-eye view as well as at the ground level in order to better appreciate the features and geography of the site, and (6) the ability to call in engineering programs to interpret the raw data such as to determine the elastic modulus of the different pavement layers from the deflection

The Virtual Environment Transportation Data Management System that was developed was a demonstration of the concept. The virtual environment uses the strength of the human mind in efficiently experiencing and understanding extensive and complex data. The VETD management system provides an environment that capitalizes on three things the human mind does well: (1) pattern recognition, (2) trend analysis, and (3) anomaly detection. Tools used to construct this environment are: (a) data visualization and (b) virtual reality.