Contents I. Introduction
Regarding the recent developments in Intelligent Transportation Systems (ITS) industry, its usage rate is gradually increasing. Basically, this system not only helps to increase safety, but also reduces the volume of traffic [1]. Amongst, the car-following models are assessed through new intelligent transport system applications [2]. These models lead us to demonstrate the effects of lane change and lengthwise movement of a driver follows other vehicles and tries to maintain in a safe distance respect to the front vehicle [2]. There are two hidden states investigated less in recent studies, named anticipation and relaxation behavior that happen for following vehicle before and after the lane change respectively [3]. Accordingly, when LC suddenly exits the certain lane, the FV unexpectedly encounters far distance from leading vehicle. Thus, it takes several seconds, that FV compensates and adjusts to a safe position [4]. According to Fig. 1, this transient state is called relaxation which is a nonlinear behaviour. Moreover, anticipation is another factor that helps driver to maintain in a safe position. Addressing anticipation behaviour, LC decides to implement its plan, and signals using indicators to make the FV aware, thus the follower is able to manage maintain an optimised lane change by decreasing the relative distance considering the safety. These factors, considerably help to control traffic, have studied less in recent researches [5]- [8]. Accordingly, they are chosen as main objective of this study, and novel Adaptive Nero-Fuzzy Interface Systems (ANFIS) are proposed for assessment [9]- [11].
