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Proposer
Eric Nimako Aidoo
Title
Decision tree-based classification of red-light violation among drivers
Goal
The aim of this is to classify red-light violations and the associated risk factors among drivers
Description
Traffic lights are one of the road transportation systems designed at the road environment to regulate competitions among road users at intersections. In the absence of traffic lights at intersections road users are at risk of road crashes. Although traffic lights serve as a medium of regulating conflicts among road users at intersections, different studies have shown that not all road users comply with the red signals. Thus, classification of red-light violation among drivers will be important to support training and policies in road transportation safety. In this study, decision tree-based model will be developed to classify red-light violations and the associated risk factors among drivers.
Resources
R programming, Statistical modelling knowledge, Machine learning knowledge.
Background
Url
Difficulty Level
Variable
Ethical Approval
None
Number Of Students
2
Supervisor
Eric Nimako Aidoo
Keywords
Degrees
Bachelor of Science in Computer Science
Master of Science in Data Science
Bachelor of Science in Statistical Data Science
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