Developping an Uncertainty Based Reasoning Approach for Bus Rapid Transit Systems Deployment Planning, Case Study: BRT Lane of Rasht City

Today in transportation and engineering applications, there are complex problems associated with uncertainty that are not solvable by conventional computational methods.Bus lanes are among the most well-known and widely used public transportation methods, which are no exception. The purpose of this study is to develop a dynamic basis inference system in order to determine the number of buses of a transit bus lane (case study is a BRT lane of Rasht city) based on the linguistic terms of the experts. For this purpose, a fuzzy inference system is proposed that can model bus dispatch with regard to environmental and climatic conditions, as well as considering inaccuracy and uncertainty and their simultaneous effect. Comparing the proposed method of this study to the current bus deployment systems in the area under study showed that using fuzzy inference system by modeling linguistic terms presented by experts, in addition to reducing waiting time for passengers, has an important role on decreasing fuel consumption and environmental pollution.