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Smart city article details
| Title | Study On The Optimization Of Conventional Public Transit Network In The Context Of Urban Rail Transit Based On Big Data Analysis |
|---|---|
| ID_Doc | 53510 |
| Authors | Zhao X.; Tan F. |
| Year | 2020 |
| Published | Proceedings - 2020 13th International Conference on Intelligent Computation Technology and Automation, ICICTA 2020 |
| DOI | http://dx.doi.org/10.1109/ICICTA51737.2020.00141 |
| Abstract | In order to give full play to the backbone role of rail transit and its overall benefits, and to create an urban public transit system integrating 'three networks'. We proposed an optimization and adjustment of the conventional public traffic network based on the basic theory of urban rail transit and conventional public traffic. Firstly, we analysis of the defects of the existing public transit network. Secondly, we analysis of interaction between rail transit and conventional public traffic. Thirdly, we analysis of interaction between conventional public traffic and slow traffic. Lastly, we proposed a selection of optimization model. The model proposed in this paper can be used as a reference for future research and advance the development of intelligent public transport and smart city. © 2020 IEEE. |
| Author Keywords | Big data; Conventional public traffic; Network optimization; Urban rail transit |
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