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Original Research
The application of geographic information system as an intelligent system towards emergency responses in road traffic accident in Ibadan
Submitted: 25 September 2020 | Published: 04 March 2021
About the author(s)
Akeem A. Audu, Federal School of Surveying, Oyo, NigeriaOlufemi F. Iyiola, Federal School of Surveying, Oyo, Nigeria
Ayobami A. Popoola, SARCHI Chair for Inclusive Cities, School of Built Environment and Development Studies, University of KwaZulu-Natal, Durban, South Africa
Bamiji M. Adeleye, Department of Urban and Regional Planning, Federal University of Technology Minna, Niger State, Nigeria; and, Department of Architecture and Physical Planning, Makerere University, Kampala, Nigeria
Samuel Medayese, Department of Town and Regional Planning, School of Built Environment and Development Studies, University of KwaZulu-Natal, Durban, South Africa
Choene Mosima, Department of Town and Regional Planning, School of Built Environment and Development Studies, University of KwaZulu-Natal, Durban, South Africa
Nunyi Blamah, Department of Town and Regional Planning, School of Built Environment and Development Studies, University of KwaZulu-Natal, Durban, South Africa
Abstract
Background: The high influx of private and public vehicles within global cities (including Ibadan) has resulted in traffic congestion within the city centre. Ibadan North-East, an urban local government area (LGA) within the metropolitan land area of Ibadan, has been experiencing automobile accidents and traffic congestion which in turn limits emergency responders.
Objectives: The broad objective of the study was to develop a digital road network database for emergency response to road traffic accident, Ibadan North East, Nigeria.
Methods: This study made use of primary and secondary data to generate spatial and non-spatial data. ArcGIS 10.3 was used to create the database, analyse data and display the results. Spatial search and network analysis were carried out using a kernel density estimated tool to generate a black-spot area within Ibadan North-East. Dijkstra’s shortest path algorithm in the ArcGIS Network Analysis was utilised to identify the closest health facility to the road traffic crash scene.
Results: The most cost-effective haven introduced route impedance and is defined as the best route. Study findings show that dynamic distance varies from the best route to an alternative route. Also, kernel density estimation reveals that crashes widely occur in the northeastern and southwestern parts of Ibadan North-East (Iwo Road and Orita-Aperin). Incorporating live traffic data using GPS technology and traffic cameras was identified to enhance road traffic data documentation and safety.
Conclusion: The study identifies GIS as a decision support system that is useful in the area of planning, mitigation, preparedness, response and recovery for decision-making in road traffic-related emergency management and emergency planning services in Ibadan.
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