Using the human effect in the development of soft computing car following models

Car following models, as the most popular microscopic traffic flow modeling, is increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. A number of factors including individual differences of age, gender, and risk-taking behavior, have been found to influence car following behavior. This paper presents a novel idea to calculate the DVU instantaneous reaction delay of Driver-Vehicle Unit (DVU). Considering the proposed idea, three input-output models are developed to estimate FV acceleration based on soft computing approaches. This idea is used to select the proper inputs and outputs to design the models. The performance of models is evaluated based on field data and compared to a number of existing car following models. The results show that new soft computing models based on instantaneous reaction delay outperformed the other car following models.