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Assessment on the Current and Future Performance of Addis Ababa Light Rail Transit Service Using Mathematical Modeling

Author(s): ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2022
Page(s): 1-12
DOI: 10.1155/2022/5097929
Abstract:

Congestion and extended passenger waiting time are some of the key issues that the Addis Ababa Light Railway Transit service (AALRT) faces. Passengers waited an average of 14.33 minutes, resulting in congestion of passengers. This is why the study set the main objective to develop an optimization model for improving AALRT service. The study began by developing the characteristics of the data to evaluate the congestion problem as part of its approach to achieving this objective. Second, on the selected station, an optimization model was constructed. Then an alternate model has been created by evaluating the previous model’s performance. Finally, without expanding the system, the researcher evaluates its effective service life. Using a combination of queuing theory and Monte Carlo simulation approach, the study used case study research methodology by taking the most congested metro station in both corridors and directions of AALRT at peak hours. Primary data were collected from each station and the relevant authority, while secondary data were conducted from the literature. The finding indicates that the congestion rate of AALRT reaches up to 25.3% and the percentage of the extra capacity of the tramcar required up to 115%. Therefore, it was found that currently adding two single tramcars could reduce the waiting time up to 9.52 minutes and the congestion up to 99%. The new model indicates the company can improve the service by increasing the number of tramcars per hour and replacing single tramcars with double tramcars up to the year 2047 without expansion of the infrastructure.

Copyright: © Getu Debebe and Belachew Asteray et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

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  • About this
    data sheet
  • Reference-ID
    10698217
  • Published on:
    11/12/2022
  • Last updated on:
    15/02/2023
 
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