Intelligent Transportation Systems

ITS Lab @ PSU

Intelligent Transportation Systems Laboratory

A broad range of diverse technologies, known collectively as intelligent transportation systems (ITS), holds the answer to many of our society's transportation problems. ITS are comprised of existing and new technologies, including information processing, sensors, communications, control, and electronics. Combining these technologies in innovative ways and integrating them into our multimodal transportation system will save lives, time, and resources.Transportation is the backbone of our society the movement of people and goods provides the foundation of our quality of life and economic prosperity. Fulfilling the need for a transportation system that is both economically sound and environmentally efficient requires a new way of looking at and solving our transportation problems. The strategy of adding more and more highway capacity neither solves our transportation problems, nor meets the broad national vision of an efficient, integrated transportation system. We focus on the integration and improvement of all modes highway, transit, bicycle, pedestrian and freight.Traffic crashes and congestion take heavy tolls in lives, lost productivity, and wasted energy. ITS enables people and goods to move more safely and efficiently through a state-of-the-art, intermodal transportation system.

 
 

Intelligent Transportation Systems Laboratory's Featured Project:

Empirical Comparison Of German And U.S. Traffic Sensor Data And Impact On Driver Assistance Systems

The objectives of this project are to conduct an empirical analysis of features of traffic dynamics and driver behavior on German and U.S. highways. The project will include a thorough literature review of recent German and U.S. analyses of traffic dynamics as well as the application of revolutionary analytical tools to empirical data archived in both Germany and the U.S. Through this analysis, an innovative comparison will be made between the behavior of German and U.S. drivers as they approach and pass through freeway bottlenecks.

This will provide, for the first time, a direct comparative analysis of German and U.S. freeway data, and will contribute toward a greater understanding of differences in driver behavior in the two countries. In turn, this understanding will allow for improved travel time estimation and forecasting which will lead toward improved traffic management, traveler information and driver assistance systems.

The study outputs will include a technical report, a software package, and two technical journal/symposium publications. Due to the availability of archived freeway data from both Germany and the U.S., a reliable methodology for empirical freeway bottleneck analysis, it is anticipated that the study objectives can be achieved in a reasonable amount of time. This study incorporates a unique methodology for processing freeway sensor data.

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