Thesis (M.Sc.) - Cairo University - Faculty of Graduate Studies For Statistical - Department of Information Systems and Technology

Generally, vehicle drivers vary when selecting one of alternative roads to reach a destination from a specific source location. There are some factors that affect such selection like traffic congestion, road average speed, and distance, number of traffic lights, safety and services. Commonly, a driver of a vehicle needs flexible approaches to represent and apply his/her preferences when selecting a road. Some of the available approaches aimed to feed the driver with the candidate roads with some information about each. Consequently, the driver scans such roads and selects the road that seems to be the best, however this approach is cumbersome, time consuming and complex task for many vehicle drivers, especially when they have their own preferences.This thesis proposes two approaches: a suitability membership function based approach and a fuzzy-rule based approach. It aims to tackle the problem of roads selection faced by almost all drivers in any city. It indirectly helps tackling the traffic jam problem. The proposed approach considers each driver{u2019}s preference which is defined in a flexible human-like manner and stored in the driver profile. Such preferences are concerned with the criteria of evaluating each candidate road, respecting the average speed, distance, safety and the available services. An illustrative case study shows the added value of the proposed approach compared with some other approaches

Issued also as CD