dc.contributor.author | Mugambwa, Robert | |
dc.date.accessioned | 2018-10-12T04:15:04Z | |
dc.date.available | 2018-10-12T04:15:04Z | |
dc.date.issued | 2018-10-11 | |
dc.identifier.citation | Mugambwa, R. (2018). Assessment of bus service travel time variability on designated bus routes in Kampala Capital City. Unpublished master’s thesis, Makerere University, Kampala, Uganda. | en_US |
dc.identifier.uri | http://hdl.handle.net/10570/6619 | |
dc.description | A dissertation submitted to the Directorate of Research and Graduate Training in partial fulfilment of the requirements for the Award of a Master’s of Science Degree in Civil Engineering of Makerere University | en_US |
dc.description.abstract | The bus transit system in Kampala is generally mixed with other traffic (Right-of-Way C) and therefore it is expected that travel times are subject to high degrees of variability. This study concentrated on collection and analysis of comprehensive data on bus travel times within Greater Kampala Metropolitan Area using GPS methodsalong the routes operated by AwakulaEnnumei.e the Gayaza and Matuggaroutes with repeated runs made for 21days in the month of June for both week days and weekends.Histograms by day of week and peak periods were developed with the objective of understanding and benchmarking the operations of public bus service.To assess variability of route travel times, this study used coefficient of variation (COV) as has been applied in previous studies. The results show rather homogeneous travel times irrespective of the route or peak period with low Coefficients of variation.
Three main causes of travel-time variability have been identified and tested in this study: temporal dimension, spatial dimension and Geometric parameters.This Studyfurther utilizes ordinary least squares multiple linear regression to develop a model with respect to the above dependent variables. The results show that it is possible to predict link travel times with 95% significant level using average link travel speed, link length, number and width lanes, number of junctions and bus stops per link, and traffic volume in the subject direction. The models explain 36.2% and 62.5% of link travel time variability. However, there was a lot of unexplained variability on Gayaza Route owing to mixed land use and disruptions resulting from construction activity on Northern Bypass. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Travel time variability | en_US |
dc.title | Assessment of bus service travel time variability on designated bus routes in Kampala Capital City | en_US |
dc.type | Thesis/Dissertation (Masters) | en_US |