prustyp/Traffic-and-Weather-data-mining-and-modeling-for-Accident-prediction

Road safety is one of the top most priority of every government and individual. Government spends billions of dollars on making great roadway infrastructure and safety certification of the vehicles, so that the lives of the people on the road will be safer. However, there are still a large number of fatal accidents occurring on the road. In the year 2018 alone, the number of fatalities on the road has increased upto 1.28 million [1]. Predicting accidents have thus become one of the widely researched topics which could be used by different agencies for optimizing traffic conditions (e.g. adding more lanes in one direction and reversing it when the condition changes), provide a dynamic route to riders using GPS and improving overall transportation infrastructure. There are a variety of dataset publicly available for this cause such as accident data, traffic event data and weather data. These datasets could be used to prepare useful classification models to predict whether a particular condition is more prone to accidents and drivers must drive with precaution.

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