Detecting Traffic Conditions Model Based On Clustering Nodes Situations In VANET

Research on the unified preview decision model for the longitudinal control of the intelligent vehicle

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/09544070211034254 ◽

2021 ◽

pp. 095440702110342

Author(s):

Guan Hsin ◽

He Fei ◽

Cui Wengfeng ◽

Jia Xin

Keyword(s):

Decision Making ◽

Safe Distance ◽

Simulation Test ◽

Longitudinal Control ◽

Design Algorithm ◽

Traffic Efficiency ◽

Traffic Conditions ◽

Model Based ◽

Distance Model ◽

Decision Making Model

Aiming at the problems of heavy workload and unstable switching process caused by the design algorithm of separate working conditions in the existing longitudinal control strategy, this paper proposes a unified preview decision-making model, which imitates human driving behavior, and comprehensively decides the optimal longitudinal acceleration through safety, legality, and evaluation indicators; in addition, for the safe distance model based on kinematics analysis that has poor traffic efficiency and does not consider the driver’s driving habits, this paper proposes a safe distance model based on the driver’s preview characteristics and a safety judgment method based on predicted lanes; the human-vehicle-road closed-loop simulation test shows that the preview decision-making proposed in this paper can meet the expected acceleration decision of various traffic conditions. The safety distance model and safety judgment method based on the preview characteristics are scientific, reasonable, and effective.

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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