Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model

Wang, Wuhong; Mao, Yan; Jin, Jing; Wang, Xiao; Guo, Heng; Ren, Xuemei; Ikeuchi, Katsushi

doi:10.2991/ijcis.2011.4.3.2

Cited by 7 publications

(1 citation statement)

References 18 publications

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“…Driving a car, which is a complex and highly dynamic behavior of humans, is the result of cognitive processes [27] containing information perception, decision-making, and subsequent motion execution [28,29]. For a driver model, it needs to reflect some driving skills and behavioral characteristics, to distinguish it from "automatic driving controllers" [30].…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method

Hu,

Yu,

Yang

et al. 2023

Electronics

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This paper proposes a data-driven human-like driver model (HDM) based on the analysis and understanding of human drivers’ behavior in path-tracking tasks. The proposed model contains a visual perception module and a decision-making module. The visual perception module was established to extract the visual inputs, including road information and vehicle motion states, which can be perceived by human drivers. The extracted inputs utilized for lateral steering decisions can reflect specific driving skills exhibited by human drivers like compensation control, preview behavior, and anticipation ability. On this basis, an adaptive neuro-fuzzy inference system (ANFIS) was adopted to design the decision-making module. The inputs of the ANFIS include the vehicle speed, lateral deviation in the near zone, and heading angle error in the far zone. The output is the steering wheel angle. ANFIS can mimic the fuzzy reasoning characteristics of human driving behavior. Next, a large amount of human driving data was collected through driving simulator experiments. Based on the data, the HDM was established. Finally, the results of the joint simulation under PreScan/MATLAB verified the superior performances of the proposed HDM.

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Section: Introductionmentioning

confidence: 99%

A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method

Hu,

Yu,

Yang

et al. 2023

Electronics

View full text Add to dashboard Cite

show abstract

A time-discrete harmonic oscillator model of human car-following

Wagner

2011

Eur. Phys. J. B

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Evolving Model for the Complex Traffic and Transportation Network Considering Self‐Growth Situation

Zhang

2012

Discrete Dynamics in Nature and Society

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It has been approved that the scale-free feature exists in various complex networks, such as the internet, the cell or the biological networks. In order to analyze the influence of the self-growth phenomenon during the growth on the structure of traffic and transportation network, we formulated an evolving model. Based on the evolving model, we prove in mathematics that, even that the self-growth situation happened, the traffic and transportation network owns the scale-free feature due to that the node degree follows a power-law distribution. A real traffic and transportation network, China domestic airline network is tested to consolidate our conclusions. We find that the airline network has a node degree distribution equivalent to the power-law of which the estimated scaling parameter is about 3.0. Moreover the standard error of the estimated scaling parameter changes according to the self-growth probability. Our findings could provide useful information for determining the optimal structure or status of the traffic and transportation network.

show abstract

Driver's various information process and multi-ruled decision-making mechanism: a fundamental of intelligent driving shaping model

Cited by 7 publications

References 18 publications

A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method

A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method

A time-discrete harmonic oscillator model of human car-following

Evolving Model for the Complex Traffic and Transportation Network Considering Self‐Growth Situation

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