Road traffic accidents analysis using association rule mining and descriptive analytics

Road accidents analysis is possible using data mining to help traffic managers make informed decisions to protect public safety. With the aim to help reduce the number of road accidents in Angeles City, Philippines. The study analysed 1438 records from January 2015 to June 2018. Data were obtained from the Angeles City Traffic Management and Enforcement Unit (ACTMEU) to describe the characteristics of the suspected motorists involved and identify frequently occurring road accident patterns. Data analysis was done using association rule mining and descriptive analytics through pivot tables. Findings reveal that there are 73 fatal and 1365 are non-fatal RAs. Males accounted for 82.19% of fatalities and 83.30% for non-fatal. Those with ages, 15-29 have suffered the highest number of accidents having 36.99% for fatal and 35.09% for non-fatal. It is also revealed that the highest number of RAs (i.e. 70 of 1438 or 4.9% occurred from 8:01PM to 12 midnight in Barangay Balibago where Tuesdays, Fridays and Saturdays account for 54.3% of the occurrences. Apparently, the same barangay has the highest number of RAs accounting for 18.64%. It was likewise revealed that Sunday is the most accident-prone day of the city having accounted for 277 of 1438 or 19.26%. Results of the study may be used in the formulation of traffic management strategies such as deployment of traffic enforcers on where and when they may be more likely needed. Consequently, this may improve road safety and positively impact the public, commuters and motorists in Angeles City.