ANFIS based modeling for overtaking maneuver trajectory in motorcycles and autos

Ghaffari, Ali; Alimardani, Fatemeh; Khodayari, Alireza; Sadati, Hossein

doi:10.1109/iccsce.2011.6190498

Cited by 10 publications

(5 citation statements)

References 23 publications

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“…These data are collected in 0.1 s intervals and any measured sample in this data set has 18 features of each vehicle in any sample time, such as the longitudinal position, the lateral position, the velocity, the acceleration, the time, the vehicle class and the front vehicle. 21 However, this data set seem to be unfiltered and have some noise artefacts; thus, they were filtered as earlier studies (see, for example, the papers by Ghaffari et al 22 and Thiemann et al 23 ). A moving-average filter is designed and applied to unfiltered data before any further data analysis.…”

Section: Discussion and Resultsmentioning

confidence: 99%

The effect of a lane change on a car-following manoeuvre: anticipation and relaxation behaviour

Ghaffari

Khodayari

Hosseinkhani

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part D:

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Car-following and lane-changing manoeuvres are the most common driving behaviour on urban roads and highways. Although these two manoeuvres have been studied extensively, the effect of a lane change on a car-following manoeuvre remains elusive. Analysing these effects leads to integration of the car-following and the lane-changing manoeuvre which has been relatively neglected. A lane-changing manoeuvre causes the immediately following driver to deviate from common car-following models to accommodate the lane changer ahead; this is called anticipation and relaxation behaviour. These behaviours are transient states which occur between two car-following behaviours owing to the lane-changing manoeuvre. In this paper, a novel adaptive neurofuzzy model is proposed for simulating the behaviour of the follower vehicle during anticipation and relaxation behaviour. Comparison between the simulation results and the field data shows that errors in the proposed model are significantly smaller and the model can describe anticipation and relaxation behaviour properly. The anticipation and relaxation model can improve current car-following model applications to enhance the safety of vehicles such as driving assistant and collision avoidance systems.

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Section: Discussion and Resultsmentioning

confidence: 99%

The effect of a lane change on a car-following manoeuvre: anticipation and relaxation behaviour

Ghaffari

Khodayari

Hosseinkhani

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…To solve the problem, in the first step, the following matrix difference Riccati equation with the corresponding terminal condition 𝑃 𝑘𝑓 is to be solved [17],…”

Section: Control Designmentioning

confidence: 99%

Path Planning and Optimal Control for Autonomous Exit Parking

Yarahmadi

Rahmanei²,

Ghaffari³

2023

Preprint

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The primary purpose of each autonomous exit parking system is to facilitate the process of exiting the vehicle, emphasizing the comfort and safety of driving in the absence of almost any human effort. In this paper, the problem of exit parking for autonomous vehicles is addressed. A nonlinear kinematic model is presented based on the geometric relationship of the vehicle velocities, and a linear time-varying discrete-time model of the vehicle is obtained for utilizing the optimal control strategy. The proposed path planning algorithm is based on the minimization of a geometric cost function. This algorithm works for ample space exit parking in Single-Maneuver and tight spaces in Multi-Maneuver exit parking. Finally, an optimal discrete-time linear quadratic control approach is hired to minimize a quadratic cost function. To evaluate the performance of the proposed algorithm, the control system is simulated by MATLAB/Simulink software. The results show that the optimal control strategy is well able to design and follow the desired path in each of the exit parking maneuvers.

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“…Such a maneuver can be viewed as a transient condition because the vehicle deviates from the conventional modeling for a certain time. The same author deals with the modeling of the overtaking path in (Ghaffari et al, 2011(Ghaffari et al, , 2011a, as one of the most demanding traffic operations.…”

Section: Safetymentioning

confidence: 99%

Application of the ANFIS model in road traffic and transportation: A literature review from 1993 to 2018

Stojčić

2019

Oper. Res. Eng. Sci. Theor. Appl.

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The paper's focus is on researching the application of the ANFIS (Adaptive Neuro Fuzzy Inference System) model in traffic and transport through a review of relevant papers. The ANFIS, as an element of artificial intelligence, is widely used in intelligent transport systems. All collected papers are divided into 7 sub-areas, namely: 1) vehicle routing, 2) traffic control at intersections with light signaling, 3) vehicle steering and control, 4) safety, 5) modeling of fuel consumption, engine performance and exhaust emissions, 6) traffic congestion prediction, and 7) other applications. For each sub-area, the analysis of the proposed models is performed with a tabular overview of respective input and output variables, while in the third section the discussion of the results is given. It is found that the steering and control of vehicles represent a sub-area with the highest percentage in the total number of examined papers, while the security applications take second place.

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ANFIS based modeling for overtaking maneuver trajectory in motorcycles and autos

Cited by 10 publications

References 23 publications

The effect of a lane change on a car-following manoeuvre: anticipation and relaxation behaviour

The effect of a lane change on a car-following manoeuvre: anticipation and relaxation behaviour

Path Planning and Optimal Control for Autonomous Exit Parking

Application of the ANFIS model in road traffic and transportation: A literature review from 1993 to 2018

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