TRANSPORTATION SYSTEM OF ADDIS ABABA IN CASE OF AKAKI KALITY SUB CITY
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Date
2020-10-15
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Hawassa University
Abstract
Parking demand model represents the available parking needs and forecast the parking
demands in the forms of mathematical equation using relatively easily accessible
parameters, which represent the real condition. This serves to plan and nourish the
continuously growing vehicular parking demands effectively and in order to provide
economically feasible parking spaces on high priced urban area lands. Due to their
physical appearance and maneuverability requirement, trucks consumed more spaces on
parking facilities. So mostly, they provided separate facility from ordinary cars. This paper
surveyed and described truck-parking areas besides proposing parking area demand
model. Through process, it incorporates extensive surveys on 12 off street parking areas to
determine the parking inventory and parking characteristics corresponding with fright
vehicle traffic and truck drivers driving manners around Akaki Kality sub city of Addis
Ababa. Using quantitative research method and data analysis on the data sourced from
primary and secondary sources through coordination of different survey methods such as
questioners; parking inventory survey forms and traffic volume studies supplemented by
statistical data analysis software have been executed. During inventory, the average area
of the studied parking facilities were founded 7817 square meters. In addition, on
infrastructural perspectives the truck parking areas were poorly organized and equipped.
Based on parking survey the average parking accumulation in studied zone was 111 trucks
with parking load 267 trucks hour and parking occupancy of 67.91%. Since the study
conducted during period of daytime traffic ban enforcement on trucks, besides showing the
increase in the efficiency of off street truck parking during that period it proposes multi liner regression model
Description
Keywords
Off-Street Parking, Parking Survey, Parking Accumulation, Parking Occupancy
