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:

Evaluating Traffic Signal Improvements for Freight Mobility

Traditional models for traffic signal control consider all vehicles in a single class and operate in a simplified mode of operation. This mode of operation is a function of the information collected by the detection and the ability of the traffic signal controller to use advanced data. The use of video detection presents new opportunities for more strategic traffic control decisions by providing preferential treatment for freight vehicles. One reference to systems minimizing truck stops at signalized intersections was found in the existing literature. The system was developed and implemented at one signalized intersection in Sullivan City, Texas in order to address the issues connected with the increased truck traffic and resulting pavement damage, traffic delay and decreased safety at a signalized intersection. (Sunkari, Charara and Urbanik, 2001). Specifically, this system had an objective to minimize stops experienced by trucks at high-speed signalized intersections. It used loop detectors and a classifier to identify trucks approaching the intersection. This information was then used by an algorithm developed by the Texas Transportation Institute to minimize truck stops and traffic delay while improving safety, reducing pavement wear, and decreasing traffic delay. The before-after analysis showed that the system would pay for itself in less than two years (Sunkari, Charara

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