Modeling Highway Traffic Safety In Nigeria Using Bayesian Network

Highway traffic safety is an issue that confronts developing countries as well as those of industrialized nations. A lot of people are injured and/or killed all over the world each day on highway traffic related crashes. Nigeria, as a developing country, has been experiencing unusually high traffic related injury and fatality rates. In order to commence combating highway safety problems in Nigeria, the first thing is to identify the major contributing factors including poor road condition, road obstruction, anemic use of traffic control devices (TCDs), driving under the influence (DUI), aggressive/reckless driving, mechanical failure, and driver fatigue. Nigeria does not have a reliable and comprehensive database of traffic accidents and fatalities. Consequently, the Delphi Technique was utilized in generating the required data such as number of registered automobiles, number of licensed drivers, and annual fatality count for modeling and forecasting accident rates in Nigeria. A Bayesian Network Model was developed and used with the data obtained from Delphi process to demonstrate possible traffic safety responses to different scenarios of changes in the Nigerian socio-political culture. The conclusions that are drawn from the Bayesian Network support the notion that the Nigerian traffic safety outlook will improve significantly if the existing laws and policies are enforced, even at a very moderate level.