An Optimal Decision Making System on Road Accident Analysis and Road Safety Enhancements

Determining road accident and provoke of the road occasion in every area is important for road safety enlargements. Earlier spatial immersion procedures did not concede the cause and asperity levels of road accidents. Applying Data-Driven Methods to ROAD Safety (DDMRS) can aid police departments designate resources more effectively. By lime-lighting on risky block, highly visible traffic law enforcement coincidently can diminish crashes. Most studies have focused on crunches after appealing new patrol paths, but few have archived how to progress or change police report time. To drastically reduce fatalities and serious cramps on roads, the ability need to review the appearance and cause of road accidents and classify the hidden information's behind the accidents using previous chronicles. For these analyses the raw data is not sufficient, so implementation of effective data excavating is obligatory.
With the use of data mining method such as decision trees will help to discover a best remedy for every scrutiny. The contemplated system familiarizes a road accident classification model. In the scheme, the system first mine associations rules of the crash data, and the detected rules will be build the decision tree named as "SDT" spatial Decision Tree, which is based on the consolidation of association rule and ID3 algorithms. Using these approaches the road accident data can be induced. And finally, the cause for the accident will be recognized for the desired effort.