A FUZZY-BASED APPROACH FOR TRAFFIC JAM DETECTION

Though many have studied choosing one of the alternative ways to reach a destination, the factors such as average road speed, distance, and number of traffic signals, traffic congestion, safety, and services still presents an indisputable challenge. This paper proposes two approaches: Appropriate membership function and ambiguous rule-based approach. It aims to tackle the route choice problem faced by almost all drivers in any city. It indirectly helps in tackling the problem of traffic congestion. The proposed approach considers the preference of each driver which is determined in a flexible way like a human and stored in the driver profile. These preferences relate to the criteria for evaluating each candidate route, considering the average speed, distance, safety, and services available. An illustrative case study demonstrates the added value of the proposed approach compared to some other approaches.