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Distributed Data Management of Daily Car Pooling Problems

Distributed Data Management of Daily Car Pooling Problems
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Author(s): Roberto Wolfler Calvo (Universitè de Technologie de Troyes, France), Fabio de Luigi (University of Ferrara, Italy), Palle Haastrup (European Commission, Italy)and Vittorio Maniezzo (University of Bologna, Italy)
Copyright: 2005
Pages: 5
Source title: Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch078

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Abstract

The increased human mobility, combined with high use of private cars, increases the load on the environment and raises issues about the quality of life. The use of private cars lends to high levels of air pollution in cities, parking problems, noise pollution, congestion, and the resulting low transfer velocity (and, thus, inefficiency in the use of public resources). Public transportation service is often incapable of effectively servicing non-urban areas, where cost-effective transportation systems cannot be set up. Based on investigations during the last years, problems related to traffic have been among those most commonly mentioned as distressing, while public transportation systems inherently are incapable of facing the different transportation needs arising in modern societies. A solution to the problem of the increased passenger and freight transportation demand could be obtained by increasing both the efficiency and the quality of public transportation systems, and by the development of systems that could provide alternative solutions in terms of flexibility and costs between the public and private ones. This is the rationale behind so-called Innovative Transport Systems (ITS) (Colorni et al., 1999), like car pooling, car sharing, dial-a-ride, park-and-ride, card car, park pricing, and road pricing, which are characterized by the exploitation of innovative organizational elements and by a large flexibility in their management (e.g., traffic restrictions and fares can vary according with the time of day).

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