Multi-Modal Agent-based Path Finding in Public Transportation System

The increasing importance of transportation in urban spaces, as well as the numerous problems it has created, have prompted decision-makers to encourage citizens to use public transportation as much as possible. Therefore, scientists and urban decision-makers are looking for a comprehensive system for more connections between transportation systems. On the other hand, the use of public transportation is very important and will create spatial justice, will bring proper access for all people. In this paper, a factor-based multiprocessor routing including taxis, buses and agencies was designed. Agents appear in the role of travelers who have the opportunity to choose any possible means of transportation to cross from origin to destination and also fill the gaps in their path by walking. The main criteria are choosing the path of time and cost along the way. Field data were collected to evaluate the results of the model. The results of analyzing the field data by multicriteria methods revealed that the priorities of people’s travelling mode are internet taxi, agency (called by telephone), bus and taxi (with predetermined rout and taking more than one passenger) with values of 0.4, 0.27, 0.19 and 0.14 respectively. The observations differed somewhat from the model output, which in fact represents optimal choices. This seems to be due to complex human decision-making in which many factors, including risk-taking and personality traits and habits and other factors, play a role.