A Group Decision Support System (GDSS) based on Naïve Bayes Classifier for Roadway Lane Management

Artificial intelligence’s objective is to replace human decision makers, while decision support system (DSS) has the aim of supporting rather than replacing .In a group DSS (GDSS) a number of managers need to be involved in the decision process. Roadway lane management can be implemented by different strategies whichever is ap-propriate for particular situation, based on the environment and individuals’ behavior. Solving lane manage-ment problem requires setting weights for different management strategies by some experts based on stand-ards on physical characteristics of the way and some other experts based on the individual's behavior. Finally, the planner(s) will choose the most appropriate strategy based on the current characteristics of the roadway and its users and also based on previous experience on that country. This article makes an environment which exerts experts' consult and for each roadway/society situation estimates fuzzy results based on this consult and previous implementation experience from knowledge base. A Naive Bayes classifier is the core of the proposed GDSS which handles the irrelevant attributes, and can get a good estimate of the probability and do not require a very large training set.