An Activity-Based Tour Generation Model with Peshawar as Case Study

Abstract

The forecasting of travel demand is an important step in the planning of an efficient transportation system. Transportation planners need accurate information about the capacity of the current system and their prediction of the future demand should have a strong basis. Earlier, Travel demand models used a statistic-based approach towards predicting travel demand which gave a macroscopic view of the problem and did not consider the decisions of an individual or the reasoning behind those decisions. However, an individual does not travel without any reason. The need for travel arises from the need to partake in different activities. A behaviour-oriented travel demand model that takes into account the behaviour of the individual is the need of the hour. In this study, an activity-based tour generation model for a small and unplanned metro area, in this case, Peshawar (Pakistan), was developed. Multinomial logistic regression was used for modelling. The results generated from the model were tallied and closely correlated with manually collected data.