Analysis of Naturalistic Driving Data

2008 ◽  
Vol 2061 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Venky Shankar ◽  
Paul P. Jovanis ◽  
Jonathan Aguero-Valverde ◽  
Frank Gross
Keyword(s):  
Statistical Models ◽  
Formal Definition ◽  
Model Formulation ◽  
Naturalistic Driving ◽  
Definition Of ◽  
Crash Surrogate ◽  
Safety Knowledge ◽  
Model Structures

Recently completed naturalistic (i.e., unobtrusive) driving studies provide safety researchers with an unprecedented opportunity to study and analyze the occurrence of crashes and a range of near-crash events. Rather than focus on the details of the events immediately before the crash, this study seeks to identify methodological paradigms that can be used to answer questions long of interest to safety researchers. In particular, an attempt is made to shed some light on the four important components of methodological paradigms for naturalistic driving analysis: surrogates, evaluative aspects related to model structures, interpretation of driving context, and assessment of risk and associated sampling issues. The methodological paradigms are founded on a formal definition of the attributes of a valid crash surrogate that can be used in model formulation and testing. After a brief summary of the type of data collected in the studies, an overall framework for the analysis and a range of specific models to test hypotheses of interest are presented. A summary is given of how the systematic analyses with statistical models can extend safety knowledge beyond an assessment of “causes” of individual crashes.

scholarly journals Students’ Understanding on Formal Definition of Limit

2021 ◽  
Vol 1752 (1) ◽  
pp. 012082
Author(s):  
Nurdin ◽  
S F Assagaf ◽  
F Arwadi
Keyword(s):  
Formal Definition ◽  
Definition Of

Diagnosis Rule Discovery Based on Causality in the Context of Fault Diagnosis in Rotating Machinery

2014 ◽  
Vol 532 ◽  
pp. 113-117
Author(s):  
Zhou Jin ◽  
Ru Jing Wang ◽  
Jie Zhang
Keyword(s):  
Fault Diagnosis ◽  
General Framework ◽  
Complex Structure ◽  
Rotating Machinery ◽  
Massive Data ◽  
Formal Definition ◽  
Rule Discovery ◽  
Rule Based ◽  
Simple Implementation ◽  
Definition Of

The rotating machineries in a factory usually have the characteristics of complex structure and highly automated logic, which generated a large amounts of monitoring data. It is an infeasible task for uses to deal with the massive data and locate fault timely. In this paper, we explore the causality between symptom and fault in the context of fault diagnosis in rotating machinery. We introduce data mining into fault diagnosis and provide a formal definition of causal diagnosis rule based on statistic test. A general framework for diagnosis rule discovery based on causality is provided and a simple implementation is explored with the purpose of providing some enlightenment to the application of causality discovery in fault diagnosis of rotating machinery.

scholarly journals Time to Harmonize Dengue Nomenclature and Classification

Viruses ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 569 ◽  
Author(s):  
Lize Cuypers ◽  
Pieter Libin ◽  
Peter Simmonds ◽  
Ann Nowé ◽  
Jorge Muñoz-Jordán ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Dengue Virus ◽  
Classification System ◽  
Formal Definition ◽  
Classification Procedure ◽  
Genotype 2 ◽  
Global Spread ◽  
Significant Burden ◽  
Definition Of ◽  
Epidemiological Characteristics

Dengue virus (DENV) is estimated to cause 390 million infections per year worldwide. A quarter of these infections manifest clinically and are associated with a morbidity and mortality that put a significant burden on the affected regions. Reports of increased frequency, intensity, and extended geographical range of outbreaks highlight the virus’s ongoing global spread. Persistent transmission in endemic areas and the emergence in territories formerly devoid of transmission have shaped DENV’s current genetic diversity and divergence. This genetic layout is hierarchically organized in serotypes, genotypes, and sub-genotypic clades. While serotypes are well defined, the genotype nomenclature and classification system lack consistency, which complicates a broader analysis of their clinical and epidemiological characteristics. We identify five key challenges: (1) Currently, there is no formal definition of a DENV genotype; (2) Two different nomenclature systems are used in parallel, which causes significant confusion; (3) A standardized classification procedure is lacking so far; (4) No formal definition of sub-genotypic clades is in place; (5) There is no consensus on how to report antigenic diversity. Therefore, we believe that the time is right to re-evaluate DENV genetic diversity in an essential effort to provide harmonization across DENV studies.

scholarly journals The parametric restrictions of the Gardner and Eberhart diallel analysis model: heterosis analysis

2000 ◽  
Vol 23 (4) ◽  
pp. 869-875 ◽  
Author(s):  
José Marcelo Soriano Viana
Keyword(s):  
Statistical Models ◽  
Combining Ability ◽  
Genetic Parameter ◽  
Diallel Analysis ◽  
Sums Of Squares ◽  
Analysis Model ◽  
Model Method ◽  
Combining Ability Analysis ◽  
Definition Of ◽  
Parameter Values

It was studied the parametric restrictions of the diallel analysis model of Griffing, method 2 (parents and F1 generations) and model 1 (fixed), in order to address the questions: i) does the statistical model need to be restricted? ii) do the restrictions satisfy the genetic parameter values? and iii) do they make the analysis and interpretation easier? Objectively, these questions can be answered as: i) yes, ii) not all of them, and iii) the analysis is easier, but the interpretation is the same as in the model with restrictions that satisfy the parameter values. The main conclusions were that: the statistical models for combining ability analysis are necessarily restricted; in the Griffing model (method 2, model 1), the restrictions relative to the specific combining ability (SCA) effects, <img src="http:/img/fbpe/gmb/v23n4/6246s1.gif" align="absmiddle"> and <img src="http:/img/fbpe/gmb/v23n4/6246s2.gif" align="absmiddle"> for all j, do not satisfy the parametric values, and the same inferences should be established from the analyses using the model with restrictions that satisfy the parametric values of SCA effects and that suggested by Griffing. A consequence of the restrictions of the Griffing model is to allow the definition of formulas for estimating the effects, their variances and the variances of contrasts of effects, as well as for calculating orthogonal sums of squares.

Concepts of Augmented Image Space and Transformed Feature Space for Efficient Visual Servoing of an “Eye-in-Hand Robot”

Robotica ◽  
1991 ◽  
Vol 9 (2) ◽  
pp. 203-212 ◽  
Author(s):  
Won Jang ◽  
Kyungjin Kim ◽  
Myungjin Chung ◽  
Zeungnam Bien
Keyword(s):  
Visual Feedback ◽  
Visual Servoing ◽  
Industrial Robot ◽  
Robot Vision ◽  
Feature Space ◽  
Image Features ◽  
Image Space ◽  
Formal Definition ◽  
Computational Burden ◽  
Definition Of

SUMMARYFor efficient visual servoing of an “eye-in-hand” robot, the concepts of Augmented Image Space and Transformed Feature Space are presented in the paper. A formal definition of image features as functionals is given along with a technique to use defined image features for visual servoing. Compared with other known methods, the proposed concepts reduce the computational burden for visual feedback, and enhance the flexibility in describing the vision-based task. Simulations and real experiments demonstrate that the proposed concepts are useful and versatile tools for the industrial robot vision tasks, and thus the visual servoing problem can be dealt with more systematically.

Notes on providing a formal definition of equivalence

2010 ◽  
Vol 10 (1-2) ◽  
pp. 143-148
Author(s):  
Gabrielle Martino
Keyword(s):  
Formal Definition ◽  
Definition Of

scholarly journals The formal definition of reference priors

2009 ◽  
Vol 37 (2) ◽  
pp. 905-938 ◽  
Author(s):  
James O. Berger ◽  
José M. Bernardo ◽  
Dongchu Sun
Keyword(s):  
Formal Definition ◽  
Reference Priors ◽  
Definition Of

scholarly journals Extraction of Naturalistic Driving Patterns with Geographic Information Systems

2020 ◽  
Author(s):  
José Balsa-Barreiro ◽  
Pedro M. Valero-Mora ◽  
Mónica Menéndez ◽  
Rashid Mehmood
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Smart Cities ◽  
Spatial Scales ◽  
Geographic Information ◽  
Small Population ◽  
Driving Patterns ◽  
Valid Data ◽  
Naturalistic Driving ◽  
Definition Of

Abstract A better understanding of Driving Patterns and their relationship with geographical driving areas could bring great benefits for smart cities, including the identification of good driving practices for saving fuel and reducing carbon emissions and accidents. The process of extracting driving patterns can be challenging due to issues such as the collection of valid data, clustering of population groups, and definition of similar behaviors. Naturalistic Driving methods provide a solution by allowing the collection of exhaustive datasets in quantitative and qualitative terms. However, exploiting and analyzing these datasets is complex and resource-intensive. Moreover, most of the previous studies, have constrained the great potential of naturalistic driving datasets to very specific situations, events, and/or road sections. In this paper, we propose a novel methodology for extracting driving patterns from naturalistic driving data, even from small population samples. We use Geographic Information Systems (GIS), so we can evaluate drivers’ behavior and reactions to certain events or road sections, and compare across situations using different spatial scales. To that end, we analyze some kinematic parameters such as speeds, acceleration, braking, and other forces that define a driving attitude. Our method favors an adequate mapping of complete datasets enabling us to achieve a comprehensive perspective of driving performance.

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