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Computational Intelligence and its Role in Enhancing Sustainable Transport Systems

Author(s): Eric Goodyer | Samad Ahmadi | Francisco Chiclana | David Elizondo | Mario Gongora | Ben Passow | Yinjie Yang

Journal: International Journal for Traffic and Transport Engineering
ISSN 2217-544X

Volume: 1;
Issue: 3;
Start page: 180;
Date: 2011;
Original page

Keywords: Computational Intelligence | Artificial Intelligence | Intelligent Transport Systems

DeMontfort University’s (DMU) Centre for Computational Intelligence (CCI) is engaged in a range of programmes applying modern Computational Intelligence (CI) techniques to provide superior analysis of complex real-time data sets that arise within transport systems. Better use of existing transport infrastructures can achieve positive sustainable outcomes, reducing congestion, improving air quality, providing real-time travel information and supporting low carbon vehicles. This is exemplified by the following examples: • ITRAQ, an integrated CI system that uses live feeds to determine the optimum use of the road system to reduce congestion and to improve air quality. • Sustainable Airport development Decision Support Systems. A CI based model that interfaces with a GIS system to model the environmental impact of flight paths. • The application of CI to solve multi-variable systems, logistics and passenger information. • VenusSim. The use of CI to model the dynamics of customer flows in transport terminals.
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