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Crash severity modelling using ordinal logistic regression approach
Isaac Ofori Asare1, Alice Constance Mensah2
1MSc Applied Statistics, Vita Verde Consult, Accra, Ghana.
Summary
Road traffic accidents are a major public health issue. Key factors influencing crash severity include vehicle type, road type, speeding, and location, necessitating enhanced enforcement and driver training.
Area of Science:
- Public Health
- Transportation Safety
- Epidemiology
Background:
- Road traffic accidents pose a significant global challenge.
- In Ghana, road accidents are recognized as a critical public health threat.
Purpose of the Study:
- To identify key factors contributing to road traffic accident severity.
- To develop a predictive model for crash severity using historical data.
Main Methods:
- Utilized an ordinal regression model.
- Analyzed a dataset from the Motor Traffic and Transport Department (1989-2019).
Main Results:
- Vehicle type, national roads, speeding, and urban/rural location significantly impact crash severity.
- Ordinal logistic regression identified these factors as key indicators.
Conclusions:
- Implementing physical enforcement, such as increased police presence and technology, is crucial.
- Enhanced driver vigilance, particularly on national roads and in urban areas, is recommended.
- Developing and enforcing clear traffic laws and sanction schemes is essential for compliance.
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