Car following process is time-varying in essence, due to the involvement of human actions. This paper develops an adaptive technique for car following modeling in a traffic flow. The proposed technique includes an online fuzzy neural network (OFNN) which is able to adapt its rule-consequent parameters to the time-varying processes. The proposed OFNN is first trained by an growing binary tree le...

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...

this paper aims to investigate a new and intricate behavior of immediate follower during the lane change of leader vehicle. accordingly, the mentioned situation is a transient state in car following behavior during which the follower vehicle considerably deviates from conventional car following models for a limited time, which is a complex state including lateral and longitudinal movement simul...

This paper aims to investigate a new and intricate behavior of immediate follower during the lane change of leader vehicle. Accordingly, the mentioned situation is a transient state in car following behavior during which the follower vehicle considerably deviates from conventional car following models for a limited time, which is a complex state including lateral and longitudinal movement simul...

the control of car following is essential due to its safety and its operational efficiency. for this purpose, this paper builds a model of car following behavior based on armax structure from a real traffic dataset and design a model predictive control (mpc) system. based on the relative distance and relative acceleration of each instant, the mpc predicts the future behavior of the leader vehic...

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 ...