Nowadays in many developing countries, urban traortation has been became as a complicated problems in urban issues, so that great amount of municipality budget has been spent for urban traortation organization. Because of organize of traffic issue, the urban managers would like to solve this problem via traortation programming. Traortation programming is one of the main fields in traffic engineering course which is trying link the social economic activities with traffic flow by the modeling methods. One of the urban traortation programming methods is traditional method which is includes four modeling stages: trip generation (trip production), trip distribution, mode choice and traffic assignment. This thesis has intended to model the trip generation (production) and trip distribution in Isfahan traortation program. Multiply linear regression and Artificial Neural Networks are used in trip production modeling. Also distribution models have been estimated by non linear regression and Artificial Neural Network. Data used in models commonly have been collected from first phase of comprehensive traortation researches of Isfahan on 2001. The evaluation of results from trip production modeling which has been estimated by multiple linear regression and Artificial Neural Network demonstrate that presented models in this case are good and they are almost in same level of efficiency. The results evacuation of trip distribution which have been estimated by heuristic logit and Artificial Neural Network models shows that efficiency of heuristic logit model was significantly higher than Artificial Neural Network.
