Classification Data for Road Accidents in Dhaka City

Public safety is seriously threatened by road accidents, which are a major global concern in urban settings. The capital of Bangladesh, Dhaka City, stands out among these locations as a perfect illustration of the complicated difficulties confronted by highly populated cities in ensuring road safety. In this paper, we have used time-series analysis to model the temporal patterns and trends in accident occurrence and machine learning algorithms to identify accident hotspots and comprehend the causes of traffic accidents. We have collected data on road accidents from Accident Research Institute (ARI) of BUET for the period 2007–2021. To forecast the likelihood of an accident occurring at a specific place, we have trained a machine learning model using this data. We have also used time-series analysis to identify trends in road accidents over time. We have found that the junction, traffic conditions, weather conditions, and lighting conditions all have an impact on the likelihood of an accident occurring. The number of traffic accidents in Dhaka City can be decreased by using our data analysis to build focused initiatives. Additionally, we can create educational campaigns to raise awareness of the factors that contribute to road accidents.