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Intelligent Transportation Systems
Abstract
The increasing need for mobility has brought about significant changes in transportation infrastructures. Inefficiencies cause enormous losses of time, decrease in the level of safety for both vehicles and pedestrians, high pollution, degradation of quality of life, and huge waste of nonrenewable fossil energy.The scope of this article is to introduce novel functionality for providing knowledge to vehicles, thus jointly managing traffic and safety. This will be achieved through the design of the proposed functionality, which, at a high level, will comprise (1) sensor networks formed by vehicles of a certain vicinity that exchange traffic-related information, (2) cognitive management functionality placed inside the vehicles for inferring knowledge and experience, and (3) cognitive management functionality in the overall transportation infrastructure. The goal of the aforementioned three main components shall be to issue directives to the drivers and the overall transportation infrastructure valuable in context handling.
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Research works printed but not linked: 16
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Metadata
- Authors
- Dimitrakopoulos, G., & Demestichas, P.
- Venue
- IEEE Vehicular Technology Magazine
- Published
- 2010-03
- Volume
- 5
- Issue
- 1
- Pages
- 77-84
- ISSN
- 1556-6072 (ISSN-L)
- OpenAlex
- W1996058270
- Cited by
- 1,055
- References
- 0
- FWCI
- 55.32
- Type
- journal article
- Language
- en
- Open access
- closed
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- Dimitrakopoulos, G., & Demestichas, P. (2010). Intelligent Transportation Systems. IEEE Vehicular Technology Magazine. https://doi.org/10.1109/mvt.2009.935537
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
