Amir Abbas Rassafi - Faculty of Engineering, Imam Khomeini International Univer- sity, Qazvin, ۳۴۱۴۹, Iran
Roohollah Rezaei - Faculty of Engineering, Imam Khomeini International University, Qazvin, ۳۴۱۴۹, Iran
Mehdi Hajizamani - MIT-Portugal Program, Instituto Superior Tcnico, Technical University of Lisbon, Lisbon, Portugal

One of the most important stages in the urban transportation planning procedure is predicting the rate of trips generated by each trac zone. Currently, multiple linear regression models are frequently used as a prediction tool. This method predicts the number of trips produced from, or attracted to each trac zone according to the values of independent variables for that zone. One of the main limitations of this method is its huge dependency on the exact prediction of independent variables in future (horizon of the plan). The other limitation is its many assumptions, which raise challenging questions of its application. The current paper attempts to use fuzzy logic and its capabilities to estimate the trip generation of urban zones. A fuzzy expert system is introduced, which is able to make suitable predictions using uncertain and inexact data. Results of the study on the data for Mashhad (Lon: ۵۹.۳۷ E, Lat: ۳۶.۱۹ N) show that this method can be a good competitor for multiple linear regression method, specially, when there is no exact data for independent variables.

Trip generation, Multiple linear regression, membership function, Fuzzy rules, Fuzzy expert system