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Innocent Ndibatya
Researcher at Makerere University
Publications - 8
Citations - 101
Innocent Ndibatya is an academic researcher from Makerere University. The author has contributed to research in topics: Taxis & Public transport. The author has an hindex of 4, co-authored 7 publications receiving 33 citations. Previous affiliations of Innocent Ndibatya include Stellenbosch University.
Papers
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Minibus taxis in Kampala's paratransit system: Operations, economics and efficiency
TL;DR: In this paper, the authors analyzed the operations and economics of Kampala's minibus taxi system and its efficiency from the passengers' and the drivers' perspectives, using "floating car data".
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Walking on sunshine: Pairing electric vehicles with solar energy for sustainable informal public transport in Uganda
TL;DR: In this paper , the authors present a generic simulation environment to assess the grid impact and charging opportunities, given the unique paratransit mobility patterns, and assess the energy requirements of electric minibus taxis, which will have a knockon effect on the region's already fragile electrical grid.
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Ray of hope for sub-Saharan Africa's paratransit: Solar charging of urban electric minibus taxis in South Africa
TL;DR: In this paper, the authors used GPS tracking and spatio-temporal data to assess the energy requirements of nine electric minibus taxis as well as the informal and formal stops at which the taxis can recharge.
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Characterizing the movement patterns of minibus taxis in Kampala's paratransit system
TL;DR: These findings could help city planners to build on the self-organizing characteristics of the minibus taxi system, and improve the mobility of travelers, by optimizing routes and the distribution of public amenities.
Mapping the informal public transport network in Kampala with smartphones : making sense of an organically evolved chaotic system in an emerging city in Sub-Saharan Africa
TL;DR: In this paper, the authors describe a mapping approach using a custom-developed smartphone application which was used to quickly and accurately capture informal transport systems for analysis and study of urban mobility where no dependable data was currently available.