<p>A contemporary approach to address the problems brought on by urban transportation is the evaluation of sustainable mobility. In metropolitan areas, electric vehicles (EVs) specifically can improve the sustainability of transportation. This research uses a Knowledge-based Artificial Network (KANM) approach to create an efficient user behavioral framework focused on the Behavioral Learning Theory (BLT) to investigate Kerala customers’ perceptions of the shift to electric automobiles. To illustrate the results, information has been gathered from publicly accessible sources and calculated using finite element design and complicated variable connection analysis. According to the research findings, consumers in metropolitan areas plan to transition to electric vehicles according to subjective and attitude standards, such as the ratio of EV sales, environmental effects, barriers, and the cost of switching to EVs. The current Distributed Optimization Algorithm (DOA), which aims to give multi-objective restrictions, is used to examine the parameters and arrive at a solution in the Kerala region. The moderating impact demonstrates that the suggested approach performs better than the current methods in calculating the switching cost and creates an enhanced trade-off.</p>