A PRACTICAL O-D MATRIX ESTIMATION MODEL BASED ON FUZZY SET THEORY FOR LARGE CITIES

Estimation of the origin-destination trip demand matrix (O-D) plays a key role in travel analysis and transportation planning and operations. Many researchers have developed different O-D matrix estimation methods using traffic counts, which allow simple data collection as opposed to the costly traditional direct estimation methods based on home and roadside interviews. In this paper, a new fuzzy O-D matrix estimation model (FODMEM) is proposed to estimate the O-D matrix from traffic count. A gradient-based algorithm, containing a fuzzy rule based approach to control the estimated O-D matrix changes, is proposed to solve FODMEM. Since link data only represents a snapshot situation, resulting in inconsistency of data and poor quality of the estimated O-D's, the proposed method considers link data as fuzzy values that vary within a certain bandwidth. An equilibrium based fuzzy assignment method is proposed to assign the estimated O-D matrix, which causes the assigned volumes to be fuzzy members. The shortest path algorithm of the proposed method is similar to the Floyd-Warshall Algorithm (FFWA). We introduce a new fuzzy comparing index to compare and estimate the distance between the assigned and observed link volumes and the model is formulated based on this index. FODMEM is implemented in Mashhad city in Iran. Real data obtained from Mashhad Comprehension Transportation Study (MCTS) are used in this study and results are presented to show high capability of FODMEM to estimate O-D matrix in large networks.