Bibliometric analysis of simulated driving research from 1997 to 2016

Neuroanatomical correlates of distracted straight driving performance: a driving simulator MRI study across the lifespan

Background

Driving is the preferred mode of transportation for adults across the healthy age span. However, motor vehicle crashes are among the leading causes of injury and death, especially for older adults, and under distracted driving conditions. Understanding the neuroanatomical basis of driving may inform interventions that minimize crashes. This exploratory study examined the neuroanatomical correlates of undistracted and distracted simulated straight driving.

Methods

One-hundred-and-thirty-eight participants (40.6% female) aged 17-85 years old (mean and SD = 58.1 ± 19.9 years) performed a simulated driving task involving straight driving and turns at intersections in a city environment using a steering wheel and foot pedals. During some straight driving segments, participants responded to auditory questions to simulate distracted driving. Anatomical T1-weighted MRI was used to quantify grey matter volume and cortical thickness for five brain regions: the middle frontal gyrus (MFG), precentral gyrus (PG), superior temporal cortex (STC), posterior parietal cortex (PPC), and cerebellum. Partial correlations controlling for age and sex were used to explore relationships between neuroanatomical measures and straight driving behavior, including speed, acceleration, lane position, heading angle, and time speeding or off-center. Effects of interest were noted at an unadjusted p-value threshold of 0.05.

Results

Distracted driving was associated with changes in most measures of straight driving performance. Greater volume and cortical thickness in the PPC and cerebellum were associated with reduced variability in lane position and heading angle during distracted straight driving. Cortical thickness of the MFG, PG, PPC, and STC were associated with speed and acceleration, often in an age-dependent manner.

Conclusion

Posterior regions were correlated with lane maintenance whereas anterior and posterior regions were correlated with speed and acceleration, especially during distracted driving. The regions involved and their role in straight driving may change with age, particularly during distracted driving as observed in older adults. Further studies should investigate the relationship between distracted driving and the aging brain to inform driving interventions.

Extended reality in the automotive sector: A bibliometric analysis of publications from 2012 to 2022

The present study aims to present a bibliometric analysis of publications related to "Extended Reality" (XR) in the automotive sector. XR is revolutionizing the industry in all fields, and the automotive is one of the sectors that has had much to gain from this technology and its components (Virtual Reality, Augmented Reality, Mixed Reality). Articles on XR in the automotive field that were published from 2012 to 2022 were retrieved from the Scopus database. Extracted items were analysed in terms of the document type, document language, year of publication, country, authors, affiliations, sources, citations, keywords, and research domains. The open-source tool VOSviewer was used to visualize trends in research on XR applied to automotive. The analyses of 1584 documents revealed that the total number of publications has continually increased over the last 11 years. The country producing most of the articles in this field was Germany, followed by the United States and China. The most productive journal is Transportation Research Part F: Traffic Psychology and Behaviour and the institution that issued most of the articles is Technical University of Munich. From the analysis of author keywords, the prominent research areas currently involving the use of XR technologies in automotive can be highlighted: virtual prototyping, design, manufacturing, sales, training, driver or pedestrian behaviour analysis, and ergonomics. More recently, terms like artificial intelligence and autonomous vehicles have started to be used more frequently in studies in the field. The current study reveals an expanding corpus of literature on XR-based applications for the automotive sector using bibliometric methods. Researchers and stakeholders can use this study as a useful reference to comprehend the big picture and the state-of-the-art in this area.

Knowledge domain and research progress in green consumption: a phase upgrade study

Green consumption (GC), as one of the important initiatives to achieve the goal of carbon peaking and carbon neutrality, has attracted widespread attention from scholars in environmental and economic fields. This article reviews the literature on GC, asking two main questions: how can GC research be analyzed from macro, meso, and micro perspectives? How have the research topics in the field of GC evolved in international and Chinese academia? This study makes a visual analysis of knowledge domain based on the literature of Web of Science Core Collection and China National Knowledge Infrastructure, so as to reveal hot topics, stage division, and research trend of GC research. The results revealed the following: GC research is in a period of rapid growth, and it is mainly distributed in developed countries dominated by the USA and in developing countries dominated by China. There is a trend of interdisciplinary research on GC, such as ecology, psychology, health, systematics, politics, and economics, which indicates that GC research has become increasingly inseparable from human survival and health, psychological acceptance, and social development. For the international academia, GC research pays more attention to the transformation of consumer psychology, while the Chinese academia is more concerned with the regulation of consumer behavior and the activation of green emotions. Considering the focus and characteristics of GC supervision, this study proposes GC 3.0 with a consumer-oriented and emphasizing green emotions and proposes future application scenarios from four aspects: government supervision, social self-regulation, enterprise demonstration, and personal self-monitoring.

Visualization and Analysis of Mapping Knowledge Domain of Heterogeneous Traffic Flow

Mapping knowledge domain (MKD) is an important application in bibliometrics, which is a method of visually presenting and explaining newly developed interdisciplinary scientific fields using data mining, information analysis, scientific measurement, and graphic rendering. This study combines applied mathematics, visual analysis technology, information science, and scientometrics to systematically analyze the development status, research distribution, and future trend of the heterogeneous traffic flow by using the MKD software tools VOSviewer and CiteSpace. Based on the MKD and Bibliometrics approaches, 4709 articles have been studied, which were published by Science Citation Index Expanded (SCIE) and Social Sciences Citation Index (SSCI) from 2004 to 2021 in the field of heterogeneous traffic flows. Firstly, this paper presents the annual numbers of articles, origin countries, main research organizations, and groups as well as the source journals on heterogeneous traffic flow studies. Then, cocitation analysis is used to divide heterogeneous traffic flow into three main research directions, which include “heterogeneous traffic flow model,” “traffic flow capacity analysis,” and “traffic flow stability analysis.” The keyword cooccurrence analysis is applied to identify five dominant clusters: “modeling and optimization methods,” “traffic flow characteristics analysis,” “driving behavior analysis,” “simulation experiment,” and “policies and barriers.” Finally, burst keywords were studied according to the publication date to present more clearly the change of research focus and direction over time.

Bibliometric Analysis of Research Studies Based on Federally Funded Children's Health Surveys

OBJECTIVE

Bibliometric analyses are commonly used to measure the productivity of researchers or institutions but rarely used to assess the scientific contribution of national surveys/datasets. We applied bibliometric methods to quantify the contributions of the National Survey of Children's Health (NSCH) and the National Survey of Children with Special Health Care Needs (NS-CSHCN) to the body of pediatric health-related research. We also examined dissemination to nonresearch audiences by analyzing media coverage of statistics and research produced from the surveys.

METHODS

We conducted a search of the Web of Science database to identify peer-reviewed articles related to the NSCH and NS-CSHCN published between 2002 and 2019. We summarized information about citation counts, publishing journals, key research areas, and institutions using the surveys. We used the Lexis Advance database Nexis to assess media coverage.

RESULTS

The publication set included 716 NSCH/NS-CSHCN journal articles published between 2002 and June 2019. These publications have in turn been cited 22,449 times, including in 1614 review articles. Over 180 journals have published NSCH/NS-CSHCN articles, and the most commonly covered research areas are in pediatrics; public, environmental and occupational health; psychology; and health care sciences and services. Over 500 institutions have used NSCH/NS-CSHCN data to publish journal articles, and over 950 news media articles have cited statistics or research produced by the surveys.

CONCLUSIONS

NSCH/NS-CSHCN data are widely used by government, academic, and media institutions. Bibliometric methods provide a systematic approach to quantify and describe the contributions to the scientific literature made possible with these data.

The Drives for Driving Simulation: A Scientometric Analysis and a Selective Review of Reviews on Simulated Driving Research

Driving behaviors and fitness to drive have been assessed over time using different tools: standardized neuropsychological, on-road and driving simulation testing. Nowadays, the great variability of topics related to driving simulation has elicited a high number of reviews. The present work aims to perform a scientometric analysis on driving simulation reviews and to propose a selective review of reviews focusing on relevant aspects related to validity and fidelity. A scientometric analysis of driving simulation reviews published from 1988 to 2019 was conducted. Bibliographic data from 298 reviews were extracted from Scopus and WoS. Performance analysis was conducted to investigate most prolific Countries, Journals, Institutes and Authors. A cluster analysis on authors' keywords was performed to identify relevant associations between different research topics. Based on the reviews extracted from cluster analysis, a selective review of reviews was conducted to answer questions regarding validity, fidelity and critical issues. United States and Germany are the first two Countries for number of driving simulation reviews. United States is the leading Country with 5 Institutes in the top-ten. Top Authors wrote from 3 to 7 reviews each and belong to Institutes located in North America and Europe. Cluster analysis identified three clusters and eight keywords. The selective review of reviews showed a substantial agreement for supporting validity of driving simulation with respect to neuropsychological and on-road testing, while for fidelity with respect to real-world driving experience a blurred representation emerged. The most relevant critical issues were the a) lack of a common set of standards, b) phenomenon of simulation sickness, c) need for psychometric properties, lack of studies investigating d) predictive validity with respect to collision rates and e) ecological validity. Driving simulation represents a cross-cutting topic in scientific literature on driving, and there are several evidences for considering it as a valid alternative to neuropsychological and on-road testing. Further research efforts could be aimed at establishing a consensus statement for protocols assessing fitness to drive, in order to (a) use standardized systems, (b) compare systematically driving simulators with regard to their validity and fidelity, and (c) employ shared criteria for conducting studies in a given sub-topic.

Research trends and hotspots related to global carbon footprint based on bibliometric analysis: 2007-2018

As an important indicator of greenhouse gas emissions, the carbon footprint (CF) has become increasingly important in recent years under the dual pressures of global warming and international commitments to mitigate its effects. This study collected 3698 papers related to CF from the Web of Science database as research samples (year 2007 to 2018). Based on CiteSpace, the knowledge base, popular topics, and research trends of CF are presented. The results show the following: (1) from 2007 to 2018, the number of articles on CF have steadily increased. (2) After spatial analysis of the literature, we found that among research institutions, the Chinese Academy of Sciences has the largest number of publications on the issue. When it comes to country, three important research forces can be identified: USA, China, and UK. (3) Research on the CF is interdisciplinary; in addition to the traditional fields of environmental, political, economics, and computing, CF research has received attention from the Physics, Materials, Chemistry, Mathematics, and animal sciences. (4) Through keyword clustering, currently popular topics in research can be roughly divided into four aspects: CF calculation methods, research scales, energy, and agriculture. (5) The CF research during the study period is divided into four stages according to the burst time and content of the burst keywords. According to the research status and trend, this paper puts forward the future research direction of carbon footprint.