Machine Learning Analysis of Informal Minibus Taxi Driving

¹ University of Johannesburg, Department of Urban and Regional Planning, Doornfontein Campus, 0184 Johannesburg, South Africa
² Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, Gipsa-Lab, F-38402 Saint Martin d’Hères, France
³ University of Johannesburg, Faculty of Science, GEMES, Auckland park Campus, 2006 Johannesburg, South Africa

^* e-mail: nomfundocele@gmail.com
^** e-mail: alain.kibangou@univ-grenoble-alpes.fr
^*** e-mail: wmusakwa@uj.ac.za

Abstract

This paper presents a machine learning analysis of driving behaviors in informal minibus taxis, focusing on both controlled and uncontrolled environments. Informal minibus taxis play a crucial role in urban transportation, particularly in developing countries, yet their driving patterns and safety implications remain under-explored. We utilize exploratory factor analysis to analyze data collected from smartphone GPS carried by a passenger of a minibus taxi, identifying key driving behaviors and patterns. Our study highlights significant differences in driving styles between controlled and uncontrolled environments, offering insights into safety and efficiency. The findings provide valuable information for policymakers, transportation planners, and technology developers aiming to enhance urban mobility and safety in the informal transport sector.