A GIS- ASSISTED PREDICTION TRAVEL DEMAND ON METRO NETWORK (BAGHDAD CASE STUDY)

Authors

  • Namir Ahmed Alkawaaz Author
  • Noor Moutaz Asmael Author

DOI:

https://doi.org/10.31272/jeasd.2018.2.51

Keywords:

Travel Demand, Metro Network, O-D Matrix, GIS, Transportation Planning, Transit Network.

Abstract

Baghdad Governorate is the most populated area in Iraq. It is experiencing rapid urbanization, economic growth, and motorization. The rapid increase in use private cars produced an increase in the traffic congestion, accidents, inadequate parking space and air pollution. Accordingly, it is important to investigate the need for a new transport policies and transportation projects based on Travel demand modeling. The present research methodology is based on update O-D matrix for Baghdad city and using it in travel forecasting to evaluate proposed urban mass rail services. In this study, three metro alternative routes were suggested, and according to demand estimation results, the best route will selected to meet future travel demand. It is concluded, peak hour ridership on proposed metro routes in the year 2014 is found to be 30000 passengers per hour per direction and the peak hour ridership on metro routes in the year 2035 reached 50000 passengers per hour per direction. On the other hand, it is concluded that travel demand on alternative route 1 equal 200000 and 400000 trips per day in two directions, while, load on alternative route 2 equal 360000 and 720000 trips per day in 2014 and 2035 respectively. It is concluded that, route alternative 2 and 1 recommended to be adopted to meet the travel demand requirements for the year 2035. The results of this study will provide the guide to the local transportation agencies to select the right decision, maximize their revenue and better allocate their resources.

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Key Dates

Published

2018-03-01

How to Cite

Ahmed Alkawaaz, N. ., & Moutaz Asmael, N. . (2018). A GIS- ASSISTED PREDICTION TRAVEL DEMAND ON METRO NETWORK (BAGHDAD CASE STUDY). Journal of Engineering and Sustainable Development, 22(2), 73-83. https://doi.org/10.31272/jeasd.2018.2.51

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