Proposed Methodology to Investigate the Metro Operation, Socio-Economic Impact, and its Revenue Using Automatic Ticket Machine Outputs
Mai M Eldeeb1, Akram S kotb2, Hany S Riad3, Ayman A. Ashour4
1Mai Moaz Eldeeb, civil department, higher technological institute 10th of Ramadan city, Egypt (Ph.D. Ain Shams university faculty of engineering)
2Akram soltan kotb, construction building, faculty of engineering and technology Arab academy for science, technology and maritime transport, Cairo.
3Hany Sobhy Riad Civil Eng. Dept. Ain Shams University Cairo, Egypt.
4Mohamed Ayman Ashour, architecture Eng. Dept. Ain Shams University Cairo, Egypt
Manuscript received on 25 August 2019. | Revised Manuscript received on 05 September 2019. | Manuscript published on 30 September 2019. | PP: 396-402 | Volume-8 Issue-11, September 2019. | Retrieval Number: K13620981119/2019©BEIESP | DOI: 10.35940/ijitee.K1362.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Automatic Ticket Machine outputs give the daily passengers’ traffic which entry from any station to exit to all stations in alphabetic arrangements. To utilize these important data for analyzing the phenomena and concluding the important predicted recommendations, a methodology was proposed within the present research paper. This method has the advantage to determine the O-D matrix for the metro passengers using its networks. The proposed methodology can be applicable to analyze, investigate, and predict the metro passenger traffic under different scenarios. To make Automatic Ticket Machine outputs in practices change the Entry- Exit Matrix from alphabetic arrangements into arranged Entry- Exit Matrix according to successive stations. The obtained results concluded the actual operation system on the platform, within the metro doors and into metro cars. In addition to investigate the socio-economic impact for metro stations finally, the corresponding revenue by applying different scenarios for every zone can be predicted.
Keywords: Automatic Ticket Machine; Revenue; Socio-Economic Impact; Metro Operation; passenger intensity
Scope of the Article: Computational Economics, Digital Photogrammetric