Addis Ababa Light Rail Transit Internal Trip Production Forecasting
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Date
2014-09
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Publisher
AAU
Abstract
This study mainly focuses on the Addis Ababa Light Rail Transit (AALRT) estimation of
residential based person internal trips which unless analyzed can affects the project
justification during the early stage of project installation, transportation planning during
operation stages, identification of markets, service planning, facility assessments and
revenue estimations.
To estimate the trips the required primary and secondary data are collected, the primary
data on locations closest to LRT routes are collected with a direct observation and
interviewing of government officials and the secondary data on socio-economic data,
census data and land use data are collected from various sources such as Central Statistics
Authority, Addis Ababa Transport Authority and Addis Ababa City Plan Institute. The
data gathered are analyzed using the Land Activity Rate or Land Use Method of trip
based model for the base year trip production calculation and Growth Factor Methods for
future trip projection calculations.
the land activity rate is used to determine the total land areas covered by the LRT routes
and the Institute for Transportation Engineers (ITE) standard is used to determine the
trips per hectare produced and finally the growth factor method is used to project the
trips for future times.
Based on these models the numbers of trips are calculated both on North-South and EastWest
LRT routes as a minimum and a maximum values in interval for the consecutive
five years. The North–South route forecasting shows a minimum of 603,159 person trips
per day and a maximum of 2,031,691 person trips per day whereas the East-West route
forecasting shows a minimum of 1,124,988 person trips per day and a maximum of
3,789,434 person trips per day generated after five years in 2019G.C.Thus from the
forecasted result of residential based internal trip production of the coming five years, the
Ethiopian Railways Corporation (ERC) will be able to carry out the supply side facility
estimation and future revenue projections so as to make the company responsive for the
changes made on the travel needs.
Description
Keywords
Light Rail Transit, Forecasting, Trip