Developing Trip Generation Model for Suburb Area of a City: Case of Kolfe Keranio Sub City, Addis Ababa
| dc.contributor.advisor | Bikila, Teklu (PhD) | |
| dc.contributor.author | Hana, Nega | |
| dc.date.accessioned | 2021-07-06T10:37:14Z | |
| dc.date.accessioned | 2023-11-11T12:53:41Z | |
| dc.date.available | 2021-07-06T10:37:14Z | |
| dc.date.available | 2023-11-11T12:53:41Z | |
| dc.date.issued | 2021-03 | |
| dc.description.abstract | The first important step of transportation planning process is trip generation modelling and followed by trip distribution, modal choice and trip assignment. It is essential for forecasting travel demand pattern by planning transportation system. Travel pattern modelling in suburban is different from urban areas because of fast population growth. This research develops a trip production model for Kolfe Keranio sub city to predict the future travel demand. The objective of research is to develop a home based trip production model for the study area using multiple linear regression and multiple classification analysis methods, then compare the performances of the methods to choice the best technique. The primary data collected using simple random sampling for 421 samples household through household interview survey from total population for model estimation and calibration within 15 travel analysis zones and analysed through SPSS software. The results of the research show that MLR and MCA used 11 and 9 significant independent variables respectively with 5 dependent variables for model estimation. Some of the significant independent variables; household size, number of employed, household income, vehicle ownership and number of student are strongly affecting trip production. From the comparison of R² value, MLR is comparatively better for modelling total, work and school trip with R² value 0.524, 0.735 and 0.772 respectively also MCA is comparatively better for modelling shopping and other trips with R² value 0.49 and 0.429 respectively. As a conclusion multiple regression method is comparatively better for trip production modelling and the research helps transport planner to use as an initial model for further development of transport planning models to forecast the travel demand for study area in the future. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/27086 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Trip Production | en_US |
| dc.subject | Multiple Linear Regression | en_US |
| dc.subject | Multiple Classification Analysis | en_US |
| dc.subject | Suburb | en_US |
| dc.subject | Kolfe Keranio sub city | en_US |
| dc.title | Developing Trip Generation Model for Suburb Area of a City: Case of Kolfe Keranio Sub City, Addis Ababa | en_US |
| dc.type | Thesis | en_US |