1999Unpublished venueRequires access

SHOWCASING ITS IN THE UNITED STATES: THE METROPOLITAN MODEL DEPLOYMENT INITIATIVE

D C Judycki, T Wilbur

Open publisher page 0 citations

Abstract

The United States Department of Transportation (DOT) has selected Phoenix, AZ, San Antonio, TX, Seattle, WA, and the New York/New Jersey/Connecticut metropolitan areas to participate in the Intelligent Transportation Systems (ITS) metropolitan Model Deployment Initiative. This initiative is considered an important step in fostering deployment of multimodal transit infrastructure across United States. The four systems are real-life showcases of how technology and information systems, along with better operations and management strategies, can improve transportation in metropolitan areas. These model deployment projects are subjected to a rigorous evaluation that will provide documentation of benefits, costs, and lessons learned. The evaluation results will be made available to other metropolitan areas so they can guide their efforts towards integrating ITS into their regional planning and programs. The article provides descriptions of the four systems chosen for the model deployment initiative.

About this research paper

What this paper is about

The United States Department of Transportation (DOT) has selected Phoenix, AZ, San Antonio, TX, Seattle, WA, and the New York/New Jersey/Connecticut metropolitan areas to participate in the Intelligent Transportation Systems (ITS) metropolitan Model Deployment Initiative. This initiative is considered an important step in fostering deployment of multimodal transit infrastructure across United States. The four systems are real-life showcases of how technology and information systems, along with better operations and management strategies, can improve transportation in metropolitan areas. These model deployment projects are subjected to a rigorous evaluation that will provide documentation of benefits, costs, and lessons learned. The evaluation results will be made available to other metropolitan areas so they can guide their efforts towards integrating ITS into their regional planning and programs. The article provides descriptions of the four systems chosen for the model deployment initiative.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The United States Department of Transportation (DOT) has selected Phoenix, AZ, San Antonio, TX, Seattle, WA, and the New York/New Jersey/Connecticut metropolitan areas to participate in the Intelligent Transportation Systems (ITS) metropolitan Model Deployment Initiative. This initiative is considered an important step in fostering deployment of multimodal transit infrastructure across United States. The four systems are real-life showcases of how technology and information systems, along with better operations and management strategies, can improve transportation in metropolitan areas. These model deployment projects are subjected to a rigorous evaluation that will provide documentation of benefits, costs, and lessons learned. The evaluation results will be made available to other metropolitan areas so they can guide their efforts towards integrating ITS into their regional planning and programs. The article provides descriptions of the four systems chosen for the model deployment initiative.

Key concepts: Software deployment, Metropolitan area, Phoenix, Documentation, Transport engineering, Intelligent transportation system, Business, Engineering management

Related papers

Back to paper searchBrowse research topicsOriginal source
SHOWCASING ITS IN THE UNITED STATES: THE METROPOLITAN MODEL DEPLOYMENT INITIATIVE — Research Paper | ScholarLens