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Optimizing the function of urban intelligent transportation system
Author(s): Qiujie Liu; Chengfu Yang
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Paper Abstract

With the development of the urban economy and the increase of car ownership, traffic congestion has become a stubborn problem in urban governance, existing road traffic and information systems are also facing severe tests, building intelligent transportation has become an urgent problem for major cities. This study focused on optimizing the function of the intelligent transportation system in the city, put forward the design of the function module of the "recommended maximum flow path in the minimum time in real time"based on the dual consideration of road network and user, and expounded its design concept, the function of intelligent decision support for query users was realized. Furthermore, in this study, the mechanism of the function realization of the proposed optimization module was analyzed and studied, that is, the concept model of the minimum time maximum flow was established, and the algorithm steps for finding the minimum time maximum flow were explored; And a simple case was analyzed. This study provides a powerful reference for the construction and improvement of intelligent transportation systems for cities.

Paper Details

Date Published: 27 November 2019
PDF: 8 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 1132119 (27 November 2019); doi: 10.1117/12.2548785
Show Author Affiliations
Qiujie Liu, Sichuan Univ. of Arts and Science (China)
Chengfu Yang, Sichuan Univ. of Arts and Science (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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