Road traffic accidents involvement among commercial taxi drivers in Nigeria: Structural equation modelling approach

Austine Taiwo, Olusegun; Asmah Hassan, Sitti; Bin Mohsin, Rahmat; Mahmud, Norashikin

doi:10.1016/j.aap.2024.107788

Accident Analysis & Prevention

2024

DOI: 10.1016/j.aap.2024.107788

|View full text |Cite

Road traffic accidents involvement among commercial taxi drivers in Nigeria: Structural equation modelling approach

Olusegun Austine Taiwo,

Sitti Asmah Hassan,

Rahmat Bin Mohsin

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Can Historical Accident Data Improve Sustainable Urban Traffic Safety? A Predictive Modeling Study

Wang,

Zhao,

Liu

2024

Sustainability

View full text Add to dashboard Cite

Traffic safety is a critical factor for the sustainable development of urban transportation systems. This study investigates the impact of historical accident information on the prediction of future traffic accident risks, as well as the interaction between this information and other features, such as driver violations and vehicle attributes. Using a comprehensive dataset of traffic accidents involving passenger vehicles in a western Chinese city, we developed two predictive models: Model 1, which is based on vehicle information and driver violations, and Model 2, which integrates historical accident data. The results indicate that the inclusion of historical accident information significantly enhances the predictive performance of the model, particularly in terms of AUC (Area Under the Curve) and AP (Average Precision) values. Furthermore, through feature importance analysis and SHAP (SHapley Additive exPlanations) value evaluation, this study reveals the interaction effects between historical accident data and other features, and how these interactions influence model decisions. The findings suggest that historical accident data play a positive role in predicting future accident risk, with varying effects on risk mitigation. These insights provide a scientific basis for developing strategies to ensure the sustainable development of urban transportation systems.

show abstract

Can Historical Accident Data Improve Sustainable Urban Traffic Safety? A Predictive Modeling Study

Wang,

Zhao,

Liu

2024

Sustainability

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Road traffic accidents involvement among commercial taxi drivers in Nigeria: Structural equation modelling approach

Cited by 1 publication

References 68 publications

Can Historical Accident Data Improve Sustainable Urban Traffic Safety? A Predictive Modeling Study

Can Historical Accident Data Improve Sustainable Urban Traffic Safety? A Predictive Modeling Study

Contact Info

Product

Resources

About