Intelligent control design of anticipation and relaxation behavior in real traffic flow

Ghaffari, Ali; Khodayari, Alireza; Hosseinkhani, Niloofar; Salehinia, Saeed

doi:10.1109/isie.2014.6864600

Cited by 2 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the errors in these two models in comparison to the acceleration of the real vehicle are shown in Figure 12 models risk for real-world applications. The standard deviation error (SDE), see equation (6), indicates the persistent error even after calibration of the model. The correlation coefficient (R 2 ), see equation 7, is another criterion that provides a measure of how well the real data are replicated.…”

Section: Discussion and Resultsmentioning

confidence: 99%

“…The anticipation and evaluation are two temporary states which occur before and after the lane-change maneuver for the following vehicle (FV). 6 According to Figure 1, when the lane-changer (LC) exits the target lane, FV is abruptly confronted with a huge space between themselves and the leader vehicle (LV), and it takes some time for FV to modify and reach the desired distance for the current speed. 7 This temporary state which starts with the reaction of FV is called evaluation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New fuzzy solution for determining anticipation and evaluation behavior during car-following maneuvers

Ghaffari

Khodayari

Kamali

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part D:

Self Cite

View full text Add to dashboard Cite

Nowadays, vehicles are the most important means of transportation in our daily lifes. During the last few decades, many studies have been carried out in the field of intelligent vehicles and significant results on the behavior of car-following and lane-change maneuvers have been achieved. However, the effects of lane-change on the car-following models have been relatively neglected. This effect is a temporary state in car-following behavior during which the follower vehicle considerably deviates from conventional car-following models for a limited time. This paper aims to investigate the behavior of the immediate follower during the lane-change of its leader vehicle. Based on a closer inspection of the microstructure behavior of real drivers, this temporary state is divided into two stages of anticipation and evaluation. Afterwards, a novel and adaptive neuro-fuzzy model that considers human driving factors is proposed to simulate the behavior of real drivers. Comparison between model results and real traffic data reveals that the proposed model can describe anticipation and evaluation behavior with smaller errors. The anticipation and evaluation model can modify current car-following models so as to accurately simulate the behavior of an immediate follower which leads to an enhancement of carfollowing applications such as driving assistance and collision avoidance systems.

show abstract

Section: Discussion and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%