Design and implementation of The Role of a Detection of vehicles’ Speed and Net Overload in Road Traffic Accident Analysis with Data Mining Approach: Case of Lagos state

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Design and implementation of The Role of a Detection of vehicles’ Speed and Net Overload in Road Traffic Accident Analysis with Data Mining Approach: Case of Lagos state

ABSTRACT

With the advent of increased transportation, overloading and overspeeding of vehicles have become the major causes of accidents and killing many lives. Transport authorities are employing advanced traffic management systems (ATMS) to improve vehicular traffic management efficiency. ATMS currently uses intelligent traffic lights and sensors distributed along the roads to achieve its goals. Furthermore, there are other promising technologies that can be applied more efficiently in place of the above-mentioned ones, such as vehicular networks. In this study, the researcher tried to assess road traffic accident causes and control mechanisms undertaken by authorities, in the Lagos state traffic police bureau and Lgos State Road Authority. As findings revealed, overload and speed have immensely contributed to the incidence of a road traffic accident in Lagos state. This research demonstrates that the Ethiopian traffic management system has been using very old systems which have very limited capacity. In this proposed work, monitoring driving behavior with the help of wireless sensor technology is the target. So, the proposed research work focused on developing a model for integrating wireless sensor networks and vehicular social networks. This paper presents a model, that can classify accidents well with better accuracy as fatal, serious, and slight or property damage was selected and evaluated. Experiment results reveal that the use of logistic regression is helpful in detecting the causes of the accident. In this work, it has been proved that driving over speed and over net load of vehicles are the major causes of traffic accidents in Lagos state and also the research proved that automation provides better performance than a human-handled system

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