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Machine Learning Analysis of Informal Minibus Taxi Driving

Domaine:

mobility

Type de record:

paper
Créateur:
CelKibMus
Éditeur:
UniDynNatPHC
Éditeur:
CCSD
Hôte:avatar
International audience 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.

Visit

hal.science

Tags

Machine leaningMinibus taxisInformal transportationDriver behaviour[STAT.ML]Statistics [stat]/Machine Learning [stat.ML][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SHS.STAT]Humanities and Social Sciences/Methods and statistics

Licenses

https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/OpenAccess

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